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1,300 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example shape parameterisation
Step1: Parameterising shapes
Three options to parameterise shapes are given below; from raw coordinates, from an RT-DICOM file, or from a Monaco® 5.10 tel... | Python Code:
import re
import numpy as np
import dicom
import matplotlib.pyplot as plt
%matplotlib inline
from electroninserts import (
parameterise_single_insert, display_parameterisation)
print("All modules and functions successfully imported.")
# !pip install --upgrade version_information
# %load_ext version_inf... |
1,301 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parallel computing using REBOUND and IPython/Jupyter
In this tutorial, we'll use IPython for parallel and distributed REBOUND simulations. With IPython, we can execute code on multi-core mac... | Python Code:
from IPython.parallel import Client
rc = Client()
print "Cluster size: %d" % len(rc.ids)
lv = rc.load_balanced_view()
lv.block = True
Explanation: Parallel computing using REBOUND and IPython/Jupyter
In this tutorial, we'll use IPython for parallel and distributed REBOUND simulations. With IPython, we can ... |
1,302 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Colaboratory
Before you start
When you open a new Colab from Github (like this one), you cannot save changes. So it's usually best to store the Colab in you personal drive "File > Save a ... | Python Code:
# YOUR ACTION REQUIRED:
# Execute this cell first using <CTRL-ENTER> and then using <SHIFT-ENTER>.
# Note the difference in which cell is selected after execution.
print('Hello world!')
Explanation: Colaboratory
Before you start
When you open a new Colab from Github (like this one), you cannot save changes... |
1,303 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Setup Software Environment
Step1: Download the Cincinnati 311 (Non-Emergency) Service Requests data
Dataset Description
Example of downloading a *.csv file progamatically using urllib2
Step... | Python Code:
from Cincinnati311CSVDataParser import Cincinnati311CSVDataParser
from csv import DictReader
import os
import re
import urllib2
Explanation: Setup Software Environment
End of explanation
data_dir = "./Data"
csv_file_path = os.path.join(data_dir, "cincinnati311.csv")
if not os.path.exists(csv_file_path):
... |
1,304 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Higgs Boson Analysis with CMS Open Data
This is an example analysis of the Higgs boson detection via the decay channel H → ZZ* → 4l
From the decay products measured at the CMS expe... | Python Code:
# Run this if you need to install Apache Spark (PySpark)
# !pip install pyspark
# Install sparkhistogram
# Note: if you cannot install the package, create the computeHistogram
# function as detailed at the end of this notebook.
!pip install sparkhistogram
# Run this to download the dataset
# See further d... |
1,305 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
entities
Step1: posting to twitter
Step2: getting access tokens for yourself | Python Code:
response=twitter.search(q="data journalism",result_type="recent",count=20)
first=response['statuses'][0]
first.keys()
first['entities']
for item in first['entities']['urls']:
print(item['expanded_url'])
for item in first['entities']['user_mentions']:
print(item['screen_name'])
cursor = twitter.curs... |
1,306 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chem 30324, Spring 2020, Homework 1
Due on January 22, 2020
Problem 1
Step1: 1. How many different 5-card hands are there? (Remember, in poker the order in which the cards are received doe... | Python Code:
import numpy as np
from scipy import linalg #contains certain operators you may need for class
import matplotlib.pyplot as plt #contains everything you need to create plots
import sympy as sy
from scipy.integrate import quad
Explanation: Chem 30324, Spring 2020, Homework 1
Due on January 22, 202... |
1,307 | Given the following text description, write Python code to implement the functionality described.
Description:
Rotate a Linked List
Link list node ; This function rotates a linked list counter - clockwise and updates the head . The function assumes that k is smaller than size of linked list . ; Let us understand the be... | Python Code:
class Node :
def __init__(self ) :
self . data = 0
self . next = None
def rotate(head_ref , k ) :
if(k == 0 ) :
return
current = head_ref
while(current . next != None ) :
current = current . next
current . next = head_ref
current = head_ref
for i in range(k - 1 ) :
c... |
1,308 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hello, LSTM!
In this project we'd like to explore the basic usage of LSTM (Long Short-Term Memory) which is a flavor of RNN (Recurrent Neural Network).
A nice theorerical tutorial is Underst... | Python Code:
%matplotlib inline
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
mpl.rc('image', interpolation='nearest', cmap='gray')
mpl.rc('figure', figsize=(20,10))
Explanation: Hello, LSTM!
In this project we'd like to explore the basic usage of LSTM (Long Short-Term Memory) which is a f... |
1,309 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Serializing STIX Objects
The string representation of all STIX classes is a valid STIX JSON object.
Step1: New in 3.0.0
Step2: If you need performance but also need human-readable output, ... | Python Code:
from stix2 import Indicator
indicator = Indicator(name="File hash for malware variant",
pattern_type="stix",
pattern="[file:hashes.md5 = 'd41d8cd98f00b204e9800998ecf8427e']")
print(indicator.serialize(pretty=True))
Explanation: Serializing STIX Objects
The string... |
1,310 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Beispiel Credit Data - Aufgabe - Klassifikation
Step1: https
Step2: Warum sollte man <b>%matplotlib inline</b> ausführen ? Recherchieren Sie !<br>
Fügen Sie<br>
<b>%matplotlib inline</b> <... | Python Code:
# hier Ihren Code einfügen und aufüühren
Explanation: Beispiel Credit Data - Aufgabe - Klassifikation:
AI, Machine Learning & Data Science
Author list: Ramon Rank
Die in KNIME durchgeführte Klassifikation der Kreditdaten soll mit Python umgesetzt werden.
Die Zellen für die Klassifikation sind bereits vorbe... |
1,311 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
First BERT Experiments
In this notebook we do some first experiments with BERT
Step1: Data
We use the same data as for all our previous experiments. Here we load the training, development a... | Python Code:
import torch
from pytorch_transformers.tokenization_bert import BertTokenizer
from pytorch_transformers.modeling_bert import BertForSequenceClassification
BERT_MODEL = 'bert-base-uncased'
BATCH_SIZE = 16 if "base" in BERT_MODEL else 2
GRADIENT_ACCUMULATION_STEPS = 1 if "base" in BERT_MODEL else 8
tokenizer... |
1,312 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
First neural network
We will build a simple feed forward neural network with Keras. We will start with a two layer neural network for simplicity.
Import all necessary python packages
Step1: ... | Python Code:
# For simple array operations
import numpy as np
# To construct the model
from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.optimizers import SGD
# Some utility for splitting data and printing the classification report
from sklearn.cross_validation import train_test... |
1,313 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Aerosol
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'csir-csiro', 'sandbox-3', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: CSIR-CSIRO
Source ID: SANDBOX-3
Topic: Aerosol
Sub-Topics: Transpor... |
1,314 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
http
Step1: Prova arrays
Step2: Riproduco cose fatte con numpy
Inizializzazioni matrici costanti
Step3: Inizializzazioni ranges e reshaping
Step4: Operazioni matriciali elementwise (somm... | Python Code:
#basic python
x = 35
y = x + 5
print(y)
#basic TF
#x = tf.random_uniform([1, 2], -1.0, 1.0)
x = tf.constant(35, name = 'x')
y = tf.Variable(x+5, name = 'y')
model = tf.global_variables_initializer()
sess = tf.Session()
sess.run(model)
print(sess.run(y))
#per scrivere il grafo
#writer = tf.summary.FileWrite... |
1,315 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parsing Los Angeles County's precinct-level results from the 2014 general election.
Step1: Load the PDF in PDFPlumber
Step2: Let's look at the first 15 characters on the first page of the ... | Python Code:
import pandas as pd
import pdfplumber
import re
Explanation: Parsing Los Angeles County's precinct-level results from the 2014 general election.
End of explanation
pdf = pdfplumber.open("2014-bulletin-first-10-pages.pdf")
print(len(pdf.pages))
Explanation: Load the PDF in PDFPlumber:
End of explanation
fir... |
1,316 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
A Parse Table for a Shift-Reduce Parser
This notebook contains the parse table that is needed for a shift reduce parser that parses the following grammar
Step1: Next, we define the action t... | Python Code:
r1 = ('E', ('E', '+', 'P'))
r2 = ('E', ('E', '-', 'P'))
r3 = ('E', ('P'))
r4 = ('P', ('P', '*', 'F'))
r5 = ('P', ('P', '/', 'F'))
r6 = ('P', ('F'))
r7 = ('F', ('(', 'E', ')'))
r8 = ('F', ('NUMBER',))
Explanation: A Parse Table for a Shift-Reduce Parser
This notebook contains the parse table that is needed ... |
1,317 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Wrangling OpenStreetMap Data with MongoDB
by Duc Vu in fulfillment of Udacity’s Data Analyst Nanodegree, Project 3
OpenStreetMap is an open project that lets eveyone use and create a free ... | Python Code:
from IPython.display import HTML
HTML('<iframe width="425" height="350" frameborder="0" scrolling="no" marginheight="0" marginwidth="0" \
src="http://www.openstreetmap.org/export/embed.html?bbox=-71.442,42.1858,-70.6984,42.4918&layer=mapnik"></iframe><br/>')
Explanation: Wrangling OpenStreetMap Data ... |
1,318 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian analysis of the Curtis Flowers trials
Copyright 2020 Allen B. Downey
License
Step1: On September 5, 2020, prosecutors in Mississippi dropped charges against Curtis Flowers, freeing... | Python Code:
# If we're running on Colab, install empiricaldist
# https://pypi.org/project/empiricaldist/
import sys
IN_COLAB = 'google.colab' in sys.modules
if IN_COLAB:
!pip install empiricaldist
# Get utils.py
import os
if not os.path.exists('utils.py'):
!wget https://github.com/AllenDowney/ThinkBayes2/raw/m... |
1,319 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AveragePooling3D
[pooling.AveragePooling3D.0] input 4x4x4x2, pool_size=(2, 2, 2), strides=None, padding='valid', data_format='channels_last'
Step1: [pooling.AveragePooling3D.1] input 4x4x4x... | Python Code:
data_in_shape = (4, 4, 4, 2)
L = AveragePooling3D(pool_size=(2, 2, 2), strides=None, padding='valid', data_format='channels_last')
layer_0 = Input(shape=data_in_shape)
layer_1 = L(layer_0)
model = Model(inputs=layer_0, outputs=layer_1)
# set weights to random (use seed for reproducibility)
np.random.seed(2... |
1,320 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Predizione sul sesso dei maratoneti di Boston
I dati si riferiscono alla maratona di Boston del 2016 e sono stati recuperato da Kaggle.
Utilizzo della libreria Pandas
La lettura e la ... | Python Code:
import pandas as pd
# E` necessario convertire il tempo di gara in secondi, per poterlo confrontare nelle regressioni
bm = pd.read_csv('./data/marathon_results_2016.csv')
bm[:3]
type(bm)
bm[['Age', 'Official Time']][:3]
bm.info()
# Vorremmo predire il sesso (label) in base all'età e al tempo ufficiale (cov... |
1,321 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Evaluate classification accuracy
This notebook demonstrates how to evaluate classification accuracy of "cross-validated" simulated communities. Due to the unique nature of this analysis, the... | Python Code:
from tax_credit.framework_functions import (novel_taxa_classification_evaluation,
extract_per_level_accuracy)
from tax_credit.eval_framework import parameter_comparisons
from tax_credit.plotting_functions import (pointplot_from_data_frame,
... |
1,322 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Python part XII (And a discussion of stochastic differential equations)
Activity 1
Step2: Programs like the Firefox browser are full of assertions
Step3: The preconditions ... | Python Code:
numbers = [1.5, 2.3, 0.7, -0.001, 4.4]
total = 0.0
for num in numbers:
assert num > 0.0, 'Data should only contain positive values'
total += num
print('total is:', total)
Explanation: Introduction to Python part XII (And a discussion of stochastic differential equations)
Activity 1: Discussion stoc... |
1,323 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Demo Gaussian Generation
Illustrate the generation of a d-dimensional Gaussian image
Description
The sequence below shows a technique to a d-dimensional Gaussian image,
understanding the dif... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
import sys,os
ia898path = os.path.abspath('/etc/jupyterhub/ia898_1s2017/')
if ia898path not in sys.path:
sys.path.append(ia898path)
import ia898.src as ia
# First case: unidimensional
# x: single valu... |
1,324 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Inclusive ML - Understanding Bias
Learning Objectives
Invoke the What-if Tool against a deployed Model
Explore attributes of the dataset
Examine aspects of bias in model results
Evaluate how... | Python Code:
!pip freeze | grep httplib2==0.18.1 || pip install httplib2==0.18.1
import os
import warnings
warnings.filterwarnings('ignore')
import numpy as np
import pandas as pd
import witwidget
from witwidget.notebook.visualization import (
WitWidget,
WitConfigBuilder,
)
pd.options.display.max_columns = 50
... |
1,325 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I'm using scipy.optimize.minimize to solve a complex reservoir optimization model (SQSLP and COBYLA as the problem is constrained by both bounds and constraint equations). There is ... | Problem:
import numpy as np
from scipy.optimize import minimize
def function(x):
return -1*(18*x[0]+16*x[1]+12*x[2]+11*x[3])
I=np.array((20,50,50,80))
x0=I
cons=[]
steadystate={'type':'eq', 'fun': lambda x: x.sum()-I.sum() }
cons.append(steadystate)
def f(a):
def g(x):
return x[a]
return g
for t in ... |
1,326 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Transfer Learning
Most of the time you won't want to train a whole convolutional network yourself. Modern ConvNets training on huge datasets like ImageNet take weeks on multiple GPUs. Instea... | Python Code:
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
vgg_dir = 'tensorflow_vgg/'
# Make sure vgg exists
if not isdir(vgg_dir):
raise Exception("VGG directory doesn't exist!")
class DLProgress(tqdm):
last_block = 0
def hook(self, block_num=1, block_size=... |
1,327 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simple RNN
In ths notebook, we're going to train a simple RNN to do time-series prediction. Given some set of input data, it should be able to generate a prediction for the next time step!
<... | Python Code:
import torch
from torch import nn
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.figure(figsize=(8,5))
# how many time steps/data pts are in one batch of data
seq_length = 20
# generate evenly spaced data pts
time_steps = np.linspace(0, np.pi, seq_length + 1)
data = np.sin(time_s... |
1,328 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Two Phase Predictions Design Pattern
The Two Phased Prediction design pattern provides a way to address the problem of keeping models for specific use cases sophisticated and performant when... | Python Code:
import numpy as np
import pandas as pd
import tensorflow_hub as hub
import tensorflow as tf
import os
import pathlib
import matplotlib.pyplot as plt
from scipy import signal
from scipy.io import wavfile
Explanation: Two Phase Predictions Design Pattern
The Two Phased Prediction design pattern provides a wa... |
1,329 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The Meterstick package provides a concise and flexible syntax to describe and execute
routine data analysis tasks. The easiest way to learn to use Meterstick is by example.
For External user... | Python Code:
!pip install meterstick
Explanation: The Meterstick package provides a concise and flexible syntax to describe and execute
routine data analysis tasks. The easiest way to learn to use Meterstick is by example.
For External users
You can open this notebook in Google Colab.
Installation
You can install from ... |
1,330 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using custom containers with Vertex AI Training
Learning Objectives
Step1: Configure environment settings
Set location paths, connections strings, and other environment settings. Make sure ... | Python Code:
!pip freeze | grep google-cloud-aiplatform || pip install google-cloud-aiplatform
import os
import time
from google.cloud import aiplatform
from google.cloud import bigquery
import pandas as pd
from sklearn.compose import ColumnTransformer
from sklearn.linear_model import SGDClassifier
from sklearn.pipelin... |
1,331 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Patient Data Analysis
Dataset gathered from stroke patients TODO ADD DETAILS ABOUT STROKE PATIENTS
Step2: Reaction Time & Accuracy
Here we include the reaction time and accuracy metr... | Python Code:
Environment setup
%matplotlib inline
%cd /lang_dec
import warnings; warnings.filterwarnings('ignore')
import hddm
import numpy as np
import matplotlib.pyplot as plt
from utils import model_tools
# Import patient data (as pandas dataframe)
patients_data = hddm.load_csv('/lang_dec/data/patients_clean.csv')
E... |
1,332 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cavity flow with Navier-Stokes
The final two steps will both solve the Navier–Stokes equations in two dimensions, but with different boundary conditions.
The momentum equation in vector form... | Python Code:
import numpy as np
from matplotlib import pyplot, cm
%matplotlib inline
nx = 41
ny = 41
nt = 1000
nit = 50
c = 1
dx = 1. / (nx - 1)
dy = 1. / (ny - 1)
x = np.linspace(0, 1, nx)
y = np.linspace(0, 1, ny)
Y, X = np.meshgrid(x, y)
rho = 1
nu = .1
dt = .001
u = np.zeros((nx, ny))
v = np.zeros((nx, ny))
p = np... |
1,333 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<!--BOOK_INFORMATION-->
<img align="left" style="padding-right
Step1: As discussed in Computation on NumPy Arrays
Step2: But this abstraction can become less efficient when computing compo... | Python Code:
import numpy as np
rng = np.random.RandomState(42)
x = rng.rand(1000000)
y = rng.rand(1000000)
%timeit x + y
Explanation: <!--BOOK_INFORMATION-->
<img align="left" style="padding-right:10px;" src="figures/PDSH-cover-small.png">
This notebook contains an excerpt from the Python Data Science Handbook by Jake... |
1,334 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced
Step1: Interactivity Options
When running in an interactive Python session, PHOEBE updates all constraints and runs various checks after each command. Although this is convenient,... | Python Code:
!pip install -I "phoebe>=2.2,<2.3"
import phoebe
b = phoebe.default_binary()
Explanation: Advanced: Optimizing Performance with PHOEBE
Setup
Let's first make sure we have the latest version of PHOEBE 2.2 installed. (You can comment out this line if you don't use pip for your installation or don't want to u... |
1,335 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Loops
Loops are a way to repeatedly execute some code. Here's an example
Step1: The for loop specifies
- the variable name to use (in this case, planet)
- the set of values to loop over (i... | Python Code:
planets = ['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune']
for planet in planets:
print(planet, end=' ') # print all on same line
Explanation: Loops
Loops are a way to repeatedly execute some code. Here's an example:
End of explanation
multiplicands = (2, 2, 2, 3, 3, 5)
p... |
1,336 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ausnahmen (Exceptions)
Was sind Ausnahmen?
Wir haben schon mehrfach festgestellt, dass beim Ausführen von Programmen Fehler aufgetreten sind, die zum Abbruch des Programms geführt haben. Das... | Python Code:
names = ['Otto', 'Hugo', 'Maria']
names[3]
Explanation: Ausnahmen (Exceptions)
Was sind Ausnahmen?
Wir haben schon mehrfach festgestellt, dass beim Ausführen von Programmen Fehler aufgetreten sind, die zum Abbruch des Programms geführt haben. Das passiert beispielsweise, wenn wir auf ein nicht existierende... |
1,337 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Visualization with Python
The following notebook serves as an introduction to data visualization with Python for the course "Data Mining".
For any comments or suggestions you can contac... | Python Code:
# Import all three librairies
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
# For displaying the plots inside Notebook
%matplotlib inline
Explanation: Data Visualization with Python
The following notebook serves as an introduction to data visualization with Python for the cours... |
1,338 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Speci... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'cnrm-cerfacs', 'sandbox-3', 'atmoschem')
Explanation: ES-DOC CMIP6 Model Properties - Atmoschem
MIP Era: CMIP6
Institute: CNRM-CERFACS
Source ID: SANDBOX-3
Topic: Atmoschem
Sub-Topics... |
1,339 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cell Cycle genes
Using Gene Ontologies (GO), create an up-to-date list of all human protein-coding genes that are know to be associated with cell cycle.
1. Download Ontologies, if necessary
... | Python Code:
# Get http://geneontology.org/ontology/go-basic.obo
from goatools.base import download_go_basic_obo
obo_fname = download_go_basic_obo()
Explanation: Cell Cycle genes
Using Gene Ontologies (GO), create an up-to-date list of all human protein-coding genes that are know to be associated with cell cycle.
1. Do... |
1,340 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SC 1 through 5 Model Comparisons
Previous analyses have been pairwise classifications (linear vs. lineage, early/late vs split/coalescence, rectangular vs. square neighbor models). Here, we... | Python Code:
import numpy as np
import networkx as nx
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import cPickle as pickle
from copy import deepcopy
from sklearn.utils import shuffle
import sklearn_mmadsen.graphs as skmg
import sklearn_mmadsen.graphics as skmplt
%matplotlib inline
# plt.st... |
1,341 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kecerdasan Buatan
Tugas 2
Step1: 1. Eksplorasi Awal Data (10 poin)
Pada bagian ini, Anda diminta untuk mengeksplorasi data latih yang diberikan. Selalu gunakan data ini kecuali diberitahuka... | Python Code:
from __future__ import print_function, division # Gunakan print(...) dan bukan print ...
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
from sklearn.datasets import load_digits
from sklearn.cluster import KMeans
from sklearn.metrics import accuracy_score, confu... |
1,342 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Table of Contents
<p><div class="lev1 toc-item"><a href="#Project-1
Step1: The data
The data consists of total population and total number of deaths due to TB (excluding HIV) in 2013 in eac... | Python Code:
# Print platform info of Python exec env.
import sys
sys.version
import warnings
warnings.simplefilter('ignore', FutureWarning)
from pandas import *
show_versions()
Explanation: Table of Contents
<p><div class="lev1 toc-item"><a href="#Project-1:-Deaths-by-tuberculosis" data-toc-modified-id="Project-1:-Dea... |
1,343 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Seaice
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify ... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'inm', 'sandbox-1', 'seaice')
Explanation: ES-DOC CMIP6 Model Properties - Seaice
MIP Era: CMIP6
Institute: INM
Source ID: SANDBOX-1
Topic: Seaice
Sub-Topics: Dynamics, Thermodynamics,... |
1,344 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matrix generation
Init symbols for sympy
Step1: Lame params
Step2: Metric tensor
${\displaystyle \hat{G}=\sum_{i,j} g^{ij}\vec{R}_i\vec{R}_j}$
Step3: ${\displaystyle \hat{G}=\sum_{i,j} g_... | Python Code:
from sympy import *
from geom_util import *
from sympy.vector import CoordSys3D
N = CoordSys3D('N')
alpha1, alpha2, alpha3 = symbols("alpha_1 alpha_2 alpha_3", real = True, positive=True)
init_printing()
%matplotlib inline
%reload_ext autoreload
%autoreload 2
%aimport geom_util
Explanation: Matrix generati... |
1,345 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="http
Step1: VSTOXX Futures & Options Data
We start by loading VSTOXX data from a pandas HDFStore into DataFrame objects (source
Step2: VSTOXX index for the first quarter of 2014.... | Python Code:
from dx import *
import numpy as np
import pandas as pd
from pylab import plt
plt.style.use('seaborn')
Explanation: <img src="http://hilpisch.com/tpq_logo.png" alt="The Python Quants" width="45%" align="right" border="4">
Implied Volatilities and Model Calibration
This setion of the documentation illustrat... |
1,346 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 使用内置方法进行训练和评估
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: 简介
本指南涵盖使用内置 API 进行训练和验证时的训练、... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
1,347 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
kafkaReceiveDataPy
This notebook receives data from Kafka on the topic 'test', and stores it in the 'time_test' table of Cassandra (created by cassandra_init.script in startup_script.sh).
``... | Python Code:
import os
os.environ['PYSPARK_SUBMIT_ARGS'] = '--conf spark.ui.port=4040 --packages org.apache.spark:spark-streaming-kafka-0-8_2.11:2.0.0,com.datastax.spark:spark-cassandra-connector_2.11:2.0.0-M3 pyspark-shell'
import time
Explanation: kafkaReceiveDataPy
This notebook receives data from Kafka on the topic... |
1,348 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step2: Q-learning is a reinforcement learning paradigm in which we learn a function
Step4: Let's run this on a dummy problem - a 5 state linear grid world with the rewards
Step5: Does it s... | Python Code:
%matplotlib inline
# Standard imports.
import numpy as np
import pylab
import scipy
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
# Resize plots.
pylab.rcParams['figure.figsize'] = 12, 7
def qlearning(reward_transition_function,
policy_function,
gam... |
1,349 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CasADi demo
What is CasADi?
A tool for quick & efficient implementation of algorithms for dynamic optimization
Open source, LGPL-licensed, <a href="http
Step1: Note 1
Step2: Functions o... | Python Code:
from pylab import *
from casadi import *
from casadi.tools import * # for dotdraw
%matplotlib inline
x = SX.sym("x") # scalar symbolic primitives
y = SX.sym("y")
z = x*sin(x+y) # common mathematical operators
print z
dotdraw(z,direction="BT")
J = jacobian(z,x)
print J
dotdraw(J,direction="BT")
Explanat... |
1,350 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting topographic arrowmaps of evoked data
Load evoked data and plot arrowmaps along with the topomap for selected time
points. An arrowmap is based upon the Hosaka-Cohen transformation a... | Python Code:
# Authors: Sheraz Khan <sheraz@khansheraz.com>
#
# License: BSD (3-clause)
import numpy as np
import mne
from mne.datasets import sample
from mne.datasets.brainstorm import bst_raw
from mne import read_evokeds
from mne.viz import plot_arrowmap
print(__doc__)
path = sample.data_path()
fname = path + '/MEG/s... |
1,351 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a name="top"></a>
<div style="width
Step1: Case Study Data
There are a number of different sites that you can utilize to access past model output analyses and even forecasts. The most robu... | Python Code:
from datetime import datetime
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from netCDF4 import Dataset, num2date
import numpy as np
from scipy.ndimage import gaussian_filter
from siphon.catalog import TDSCatalog
from siphon.ncss import NCSS
import matplotlib.pyplot as plt
import metpy.calc... |
1,352 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Reading QM outputs - EDA and COVP calculations
Step1: Normally, one would want a very generalized way of reading in output files (like an argparse input argument with nargs='+' that gets lo... | Python Code:
from __future__ import print_function
from __future__ import division
import numpy as np
Explanation: Reading QM outputs - EDA and COVP calculations
End of explanation
outputfilepath = "../qm_files/drop_0001_1qm_2mm_eda_covp.out"
Explanation: Normally, one would want a very generalized way of reading in ou... |
1,353 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
UpSampling1D
[convolutional.UpSampling1D.0] size 2 upsampling on 3x5 input
Step1: [convolutional.UpSampling1D.1] size 3 upsampling on 4x4 input
Step2: export for Keras.js tests | Python Code:
data_in_shape = (3, 5)
L = UpSampling1D(size=2)
layer_0 = Input(shape=data_in_shape)
layer_1 = L(layer_0)
model = Model(inputs=layer_0, outputs=layer_1)
# set weights to random (use seed for reproducibility)
np.random.seed(230)
data_in = 2 * np.random.random(data_in_shape) - 1
result = model.predict(np.arr... |
1,354 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matriks dengan Numpy
Matriks dengan Numpy
Numpy, sebagai salah satu library yang saling penting di pemrograman yang menggunakan matematika dan angka, memberikan kemudahan dalam melakukan ope... | Python Code:
import numpy as np
Explanation: Matriks dengan Numpy
Matriks dengan Numpy
Numpy, sebagai salah satu library yang saling penting di pemrograman yang menggunakan matematika dan angka, memberikan kemudahan dalam melakukan operasi aljabar matriks. Bila deklarasi array a = [[1,0],[0,1]] memberikan array 2D bias... |
1,355 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
KNN
$$
a(x, X^l) = \arg \max_{y \in Y} \sum_{i = 1}^{l}[y_i = y] ~ w(i, x)
$$
Step1: Wine | Python Code:
np.random.seed(13)
n = 100
df = pd.DataFrame(
np.vstack([
np.random.normal(loc=0, scale=1, size=(n, 2)),
np.random.normal(loc=3, scale=2, size=(n, 2))
]), columns=['x1', 'x2'])
df['target'] = np.hstack([np.ones(n), np.zeros(n)]).T
plt.scatter(df.x1, df.x2, c=df.target, s=100, edgeco... |
1,356 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Registration Errors, Terminology and Interpretation <a href="https
Step1: FLE, FRE, TRE empirical experimentation
In the following cell you will use a user interface to experiment with the ... | Python Code:
import SimpleITK as sitk
import numpy as np
import copy
%matplotlib notebook
from gui import PairedPointDataManipulation, display_errors
import matplotlib.pyplot as plt
from registration_utilities import registration_errors
Explanation: Registration Errors, Terminology and Interpretation <a href="https://m... |
1,357 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
You are currently looking at version 1.2 of this notebook. To download notebooks and datafiles, as well as get help on Jupyter notebooks in the Coursera platform, visit the Jupyter Notebook ... | Python Code:
import pandas as pd
df = pd.read_csv('olympics.csv', index_col=0, skiprows=1)
for col in df.columns:
if col[:2]=='01':
df.rename(columns={col:'Gold'+col[4:]}, inplace=True)
if col[:2]=='02':
df.rename(columns={col:'Silver'+col[4:]}, inplace=True)
if col[:2]=='03':
df.ren... |
1,358 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Train a ready to use TensorFlow model with a simple pipeline
Step1: BATCH_SIZE might be increased for modern GPUs with lots of memory (4GB and higher).
Step2: Create a dataset
MNIST is a d... | Python Code:
import os
import sys
import warnings
warnings.filterwarnings("ignore")
import numpy as np
import matplotlib.pyplot as plt
# the following line is not required if BatchFlow is installed as a python package.
sys.path.append("../..")
from batchflow import Pipeline, B, C, D, F, V
from batchflow.opensets import... |
1,359 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Translating between Currencies
Step1: Translating between currencies requires a number of different choices
do you want to consider the relative value of two currencies based on Market Exch... | Python Code:
from salamanca.currency import Translator
Explanation: Translating between Currencies
End of explanation
xltr = Translator()
Explanation: Translating between currencies requires a number of different choices
do you want to consider the relative value of two currencies based on Market Exchange Rates or Purc... |
1,360 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Land
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify do... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'mpi-m', 'icon-esm-lr', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: MPI-M
Source ID: ICON-ESM-LR
Topic: Land
Sub-Topics: Soil, Snow, Vegetation,... |
1,361 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Stochastic Matrices
These guys are matrices that predict a probability distribution iteratively. You present a "current" distribution, then you multiply by the "transition matrix" and it te... | Python Code:
#
# define a transition matrix
#
T = np.array([[0.1, 0.2, 0.3],
[0.5,0.3,0.6],
[0.4,0.5,0.1]])
T
#
# Start out with a random prob distribution vector
#
x0 = np.array([np.random.rand(3)]).T
x0 = x0/x0.sum()
x0
x1 = T.dot(x0)
x1
x2 = T.dot(x1)
x2
x3 = T.dot(x2)
x3
xn = x3
for i in r... |
1,362 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Predicting the house prices data set for king county
Loading graphlab
Step1: Load some house sales data
Dataset is from house sales in King County, the region where the city of Seattle, WA ... | Python Code:
import graphlab
Explanation: Predicting the house prices data set for king county
Loading graphlab
End of explanation
sales = graphlab.SFrame('home_data.gl/')
sales.head(5)
Explanation: Load some house sales data
Dataset is from house sales in King County, the region where the city of Seattle, WA is locate... |
1,363 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Simplified Selenium Functions
For example, if you are using Selenium in your automated functional tests,
instead of coding directly in Selenium like this
Step1: You can alternatively use Ma... | Python Code:
from selenium import webdriver
browser = webdriver.Firefox()
browser.get('https://python.org.')
download = browser.find_element_by_link_text('Downloads')
download.click()
download = browser.find_element_by_id('downloads')
ul = download.find_element_by_tag_name('ul')
lis = ul.find_elements_by_tag_name('li')... |
1,364 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Access a Database with Python - Iris Dataset
The Iris dataset is a popular dataset especially in the Machine Learning community, it is a set of features of 50 Iris flowers and their classif... | Python Code:
import os
data_iris_folder_content = os.listdir("./iris-species")
error_message = "Error: sqlite file not available, check instructions above to download it"
assert "database.sqlite" in data_iris_folder_content, error_message
Explanation: Access a Database with Python - Iris Dataset
The Iris dataset is a p... |
1,365 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Rock, Paper & Scissors with TensorFlow Hub - TFLite
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
1,366 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression
This notebook covers multi-variate "linear regression". We'll be going over how to use the scikit-learn regression model, as well as how to train the regressor using the fit() met... | Python Code:
import numpy as np
import pandas as pd
from pandas import Series, DataFrame
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('whitegrid')
%matplotlib inline
Explanation: Regression
This notebook covers multi-variate "linear regression". We'll be going over how to use the scikit-learn reg... |
1,367 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Team
Step1: Import non-standard libraries (install as needed)
Step2: Optional directory creation
Step3: Is the ESRI Shapefile driver available?
Step4: Define a function which will create... | Python Code:
from numpy import mean
import os
from os import makedirs,chdir
from os.path import exists
Explanation: Team: Satoshi Nakamoto <br>
Names: Alex Levering & Hèctor Muro <br>
Lesson 10 Exercise solution
Import standard libraries
End of explanation
from osgeo import ogr,osr
import folium
import simplekml
Explan... |
1,368 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This demo shows the method proposed in "Zhou, Bolei, et al. "Learning Deep Features for Discriminative Localization." arXiv preprint arXiv
Step1: Set the image you want to test and the clas... | Python Code:
# -*- coding: UTF-8 –*-
import matplotlib.pyplot as plt
%matplotlib inline
from IPython import display
import os
ROOT_DIR = '.'
import sys
sys.path.insert(0, os.path.join(ROOT_DIR, 'lib'))
import cv2
import numpy as np
import mxnet as mx
import matplotlib.pyplot as plt
Explanation: This demo shows the meth... |
1,369 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
E-Commerce data with Neural network
In this note, I am going to use neural network to analyze a e-commerce data. The data is from Udemy
Step1: The 2nd and 3rd column is numeric and need to ... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt # Plotting library
from sklearn.utils import shuffle
# Allow matplotlib to plot inside this notebook
%matplotlib inline
# Set the seed of the numpy random number generator so that the result is reproducable
np.random.seed(seed=1)
# che... |
1,370 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The MNIST dataset
The MNIST database of handwritten digits, available at Yann Lecun web site, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a la... | Python Code:
# import the mnist class
from mnist import MNIST
# init with the 'data' dir
mndata = MNIST('./data')
# Load data
mndata.load_training()
mndata.load_testing()
# The number of pixels per side of all images
img_side = 28
# Each input is a raw vector.
# The number of units of the network
# corresponds t... |
1,371 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Background information on filtering
Here we give some background information on filtering in general, and
how it is done in MNE-Python in particular.
Recommended reading for practical applic... | Python Code:
import numpy as np
from numpy.fft import fft, fftfreq
from scipy import signal
import matplotlib.pyplot as plt
from mne.time_frequency.tfr import morlet
from mne.viz import plot_filter, plot_ideal_filter
import mne
sfreq = 1000.
f_p = 40.
flim = (1., sfreq / 2.) # limits for plotting
Explanation: Backgrou... |
1,372 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing CHIRPS and ARC2 Precipitation Data in Kenya
In this demo we are comparing two historical precipitation datasets - CHIRPS and ARC2.
Climate Hazards Group InfraRed Precipitation with... | Python Code:
%matplotlib notebook
import numpy as np
from dh_py_access import package_api
import dh_py_access.lib.datahub as datahub
import xarray as xr
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
from po_data_process import get_data_in_pandas_dataframe, make_plot,get_comparison_graph
impor... |
1,373 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Blue Sky Run Engine
Contents
Step1: The Run Engine processes messages
A message has four parts
Step2: Moving a motor and reading it back is boring. Let's add a detector.
Step4: There is t... | Python Code:
from bluesky import Mover, SynGauss, Msg, RunEngine
motor = Mover('motor', ['pos'])
det = SynGauss('det', motor, 'pos', center=0, Imax=1, sigma=1)
Explanation: Blue Sky Run Engine
Contents:
The Run Engine processes messages
There is two-way communication between the message generator and the Run Engine
Con... |
1,374 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Numpy
Step1: If we want to multiply each number in that list by 3, we can certainly do it by looping through and multiplying each individual number by 3, but that seems like way too much wo... | Python Code:
a = [1,2,3]
b = 3*a
print b
Explanation: Numpy: "number" + "python"
Numpy is a Python package that is commonly used by scientists. You can already do some math in Python by itself, but Numpy makes things even easier.
We've already seen that Python has data structures such as lists, tuples, and dictionaries... |
1,375 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experiment
Step1: Load and check data
Step2: ## Analysis
Experiment Details
Step3: What are optimal levels of hebbian and weight pruning
Step4: No relevant difference | Python Code:
%load_ext autoreload
%autoreload 2
import sys
sys.path.append("../../")
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
import glob
import tabulate
import pprint
import click
import numpy as np
import pandas as pd
from ray.tune.commands... |
1,376 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Capacity of the Binary-Input AWGN (BI-AWGN) Channel
This code is provided as supplementary material of the OFC short course SC468
This code illustrates
* Calculating the capacity of the bina... | Python Code:
import numpy as np
import scipy.integrate as integrate
import matplotlib.pyplot as plt
Explanation: Capacity of the Binary-Input AWGN (BI-AWGN) Channel
This code is provided as supplementary material of the OFC short course SC468
This code illustrates
* Calculating the capacity of the binary input AWGN cha... |
1,377 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Idea
Get data
- Calculate the name length
- Calculate the chr set
- Calculate the chr set length
- Calculate the ratio for the chr set length and the name length
- Remove the duplicate lette... | Python Code:
names_df = pd.read_csv("./IMA_mineral_names.txt", sep=',', header=None, names=['names'])
names_df['names'] = names_df['names'].str.strip().str.lower()
names_df['len'] = names_df['names'].str.len()
names_df['tuple'] = names_df['names'].apply(lambda x: tuple(sorted(set(x))))
names_df['setlen'] = names_df['tu... |
1,378 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Metacritic and ROI Analysis
Step1: Load Dataset
Step2: Metacritic Ratings Representation
Step3: ROI Representation
Step4: Save Dataset
Step5: Metacritic VS. ROI
Step6: We can see that ... | Python Code:
%matplotlib inline
import configparser
import os
import requests
from tqdm import tqdm
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
from scipy import sparse, stats, spatial
import scipy.sparse.linalg
from sklearn import preprocessing, decomposition
i... |
1,379 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
L7CA - Lesson7 CAM
2018/1/23 02
Step1: The version of resnet that happens to be the best is the preact resnet. They have different internal orderings of conv,pool,res,bn,relu,etc.
We want t... | Python Code:
%reload_ext autoreload
%autoreload 2
%matplotlib inline
from fastai.imports import *
from fastai.transforms import *
from fastai.conv_learner import *
from fastai.model import *
from fastai.dataset import *
from fastai.sgdr import *
PATH = 'data/dogscats/'
sz = 224
arch = resnet34
bs = 32
m = arch(True)
m
... |
1,380 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a id='intro'></a>
Introduction
The overall goal of this project is to build a word recognizer for American Sign Language video sequences, demonstrating the power of probabalistic models. I... | Python Code:
import math
import numpy as np
import pandas as pd
from asl_data import AslDb
asl = AslDb() # initializes the database
asl.df.head() # displays the first five rows of the asl database, indexed by video and frame
asl.df.ix[98,1] # look at the data available for an individual frame
Explanation: <a id='intro... |
1,381 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Wi-Fi Fingerprinting Experiments
Import modules and set up the environment
Step1: Helper Functions
Step2: Load the model classes
A class responsible for loading a JSON file (or all the JSO... | Python Code:
# Python Standard Library
import getopt
import os
import sys
import math
import time
import collections
import random
# IPython
from IPython.display import display
# pandas
import pandas as pd
pd.set_option("display.max_rows", 10000)
pd.set_option("display.max_columns", 10000)
# Matplotlib
%matplotlib inli... |
1,382 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Training a ConvNet PyTorch
In this notebook, you'll learn how to use the powerful PyTorch framework to specify a conv net architecture and train it on the CIFAR-10 dataset.
Step2: What's th... | Python Code:
import torch
import torch.nn as nn
import torch.optim as optim
from torch.autograd import Variable
from torch.utils.data import DataLoader
from torch.utils.data import sampler
import torchvision.datasets as dset
import torchvision.transforms as T
import numpy as np
import timeit
import os
os.chdir(os.getcw... |
1,383 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CM360 Report
Create a CM report from a JSON definition.
License
Copyright 2020 Google LLC,
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in... | Python Code:
!pip install git+https://github.com/google/starthinker
Explanation: CM360 Report
Create a CM report from a JSON definition.
License
Copyright 2020 Google LLC,
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a co... |
1,384 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
From Tensor SkFlow
Step1: Load Iris Data
Step2: Initialize a deep neural network autoencoder
Step3: Fit with Iris data | Python Code:
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import random
from sklearn.pipeline import Pipeline
from chainer import optimizers
from commonml.skchainer import MeanSquaredErrorRegressor, AutoEncoder
from tensorflow.contrib.learn import datasets... |
1,385 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Convolutional Networks
So far we have worked with deep fully-connected networks, using them to explore different optimization strategies and network architectures. Fully-connected net... | Python Code:
# As usual, a bit of setup
import numpy as np
import matplotlib.pyplot as plt
from cs231n.classifiers.cnn import *
from cs231n.data_utils import get_CIFAR10_data
from cs231n.gradient_check import eval_numerical_gradient_array, eval_numerical_gradient
from cs231n.layers import *
from cs231n.fast_layers impo... |
1,386 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: script available on GitHub
Installation and Setup
Installation
Refer to this how-to.
Manage Python Packages
Python has its own package manager "pip" to keep Python self-contained. pip... | Python Code:
# I don't know how to write a program but I am charming,
# so I will write down the equations to be implemented
# and find a friend to write it :)
It is annoying to have to start each comment with a #,
triple quotation allows multi-line comments.
It is always a good idea to write lots of comment... |
1,387 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Artificial Intelligence & Machine Learning
Tugas 3
Step1: 1. Dynamic Programming (5 poin)
Seorang pria di Australia pada tahun 2017 memesan 200 McNuggets melalui drive-through hingga dilipu... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
plt.rcParams = plt.rcParamsOrig
Explanation: Artificial Intelligence & Machine Learning
Tugas 3: Search & Reinforcement Learning
Mekanisme
Anda hanya diwajibkan untuk mengumpulkan file ini saja ke uploader yang dis... |
1,388 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
\title{myHDL Sawtooth Wave Generator based on the Phase Accumulation method}
\author{Steven K Armour}
\maketitle
This is a simple SawTooth wave generator based on the phase accumulation meth... | Python Code:
from myhdl import *
import pandas as pd
from myhdlpeek import Peeker
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from sympy import *
init_printing()
Explanation: \title{myHDL Sawtooth Wave Generator based on the Phase Accumulation method}
\author{Steven K Armour}
\maketitle
This ... |
1,389 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Now let's look at some classification methods.
Nearest Neighbor
Step2: Exercise
Step3: Exercise
Step4: Now write a loop that does this using 100 different randomly generated datas... | Python Code:
# adapted from http://scikit-learn.org/stable/auto_examples/neighbors/plot_classification.html#example-neighbors-plot-classification-py
n_neighbors = 30
# step size in the mesh
# Create color maps
cmap_light = ListedColormap(['#FFAAAA', '#AAFFAA'])
cmap_bold = ListedColormap(['#FF0000', '#00FF00'])
clf = ... |
1,390 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Continuous training pipeline with Kubeflow Pipeline and AI Platform
Learning Objectives
Step6: NOTE
Step7: The custom components execute in a container image defined in base_image/Dockerfi... | Python Code:
!grep 'BASE_IMAGE =' -A 5 pipeline/covertype_training_pipeline.py
Explanation: Continuous training pipeline with Kubeflow Pipeline and AI Platform
Learning Objectives:
1. Learn how to use Kubeflow Pipeline (KFP) pre-build components (BiqQuery, AI Platform training and predictions)
1. Learn how to use KFP l... |
1,391 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introducing the Keras Functional API
Learning Objectives
1. Understand embeddings and how to create them with the feature column API
1. Understand Deep and Wide models and when to use th... | Python Code:
import datetime
import os
import shutil
import numpy as np
import pandas as pd
import tensorflow as tf
from matplotlib import pyplot as plt
from tensorflow import feature_column as fc
from tensorflow import keras
from tensorflow.keras import Model
from tensorflow.keras.callbacks import TensorBoard
from ten... |
1,392 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Proteins example recreated in python from
https
Step1: note numpy also has recfromcsv() and pandas can read_csv, with pandas DF.values giving a numpy array
Step2: Samples clustering using ... | Python Code:
import numpy as np
from numpy import genfromtxt
data = genfromtxt('http://www.biz.uiowa.edu/faculty/jledolter/DataMining/protein.csv',delimiter=',',names=True,dtype=float)
Explanation: Proteins example recreated in python from
https://rstudio-pubs-static.s3.amazonaws.com/33876_1d7794d9a86647ca90c4f182df93f... |
1,393 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Modelos Bayesianos
Aplicar um modelo estatístico a um conjunto de dados significa interpretá-lo como um conjunto de realizações de um experimento randomizado. Isso permite associar o conjunt... | Python Code:
# Inicializacao
%matplotlib inline
import numpy as np
from matplotlib import pyplot as plt
# Abrindo conjunto de dados
import csv
with open("biometria.csv", 'rb') as f:
dados = list(csv.reader(f))
rotulos_volei = [d[0] for d in dados[1:-1] if d[0] is 'V']
rotulos_futebol = [d[0] for d in dados[1:-... |
1,394 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian model selection and linear regression
This notebook uses Bayesian selection for linear regression with basis functions in order to (partially) answer question #2231975 in Math Stack... | Python Code:
import sys
sys.path.append("../src/")
from Hypotheses import *
from ModelSelection import LinearRegression
from Plots import updateMAPFitPlot, updateProbabilitiesPlot
import numpy as np
from sklearn import preprocessing
import matplotlib.pyplot as pl
%matplotlib notebook
Explanation: Bayesian model selecti... |
1,395 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
How to defer evaluation of f-strings
It seems that one solution is to use lambdas, which are explored below.
What other solutions are there?
Imagine that one wants to format a string
selecti... | Python Code:
year, month, day = 'hello', -1, 0
date_formats = {
'iso': f'{year}-{month:02d}-{day:02d}',
'us': f'{month}/{day}/{year}',
'other': f'{day} {month} {year}',
}
Explanation: How to defer evaluation of f-strings
It seems that one solution is to use lambdas, which are explored below.
What other solu... |
1,396 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating a model from scratch
We describe here how to generate a simple history file for computation with Noddy using the functionality of pynoddy. If possible, it is advisable to generate t... | Python Code:
from matplotlib import rc_params
from IPython.core.display import HTML
css_file = 'pynoddy.css'
HTML(open(css_file, "r").read())
import sys, os
import matplotlib.pyplot as plt
# adjust some settings for matplotlib
from matplotlib import rcParams
# print rcParams
rcParams['font.size'] = 15
# determine path ... |
1,397 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Computing a covariance matrix
Many methods in MNE, including source estimation and some classification
algorithms, require covariance estimations from the recordings.
In this tutorial we cov... | Python Code:
import os.path as op
import mne
from mne.datasets import sample
Explanation: Computing a covariance matrix
Many methods in MNE, including source estimation and some classification
algorithms, require covariance estimations from the recordings.
In this tutorial we cover the basics of sensor covariance compu... |
1,398 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Intro
The TV show Silicon Valley had an app called "See Food" that promised to identify food.
In this notebook, you will write code using and comparing pre-trained models to choose one as a... | Python Code:
import os
from os.path import join
hot_dog_image_dir = '../input/hot-dog-not-hot-dog/seefood/train/hot_dog'
hot_dog_paths = [join(hot_dog_image_dir,filename) for filename in
['1000288.jpg',
'127117.jpg']]
not_hot_dog_image_dir = '../input/hot-dog-no... |
1,399 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ordinary Differential Equations Exercise 1
Imports
Step2: Lorenz system
The Lorenz system is one of the earliest studied examples of a system of differential equations that exhibits chaotic... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
Explanation: Ordinary Differential Equations Exercise 1
Imports
End of explanation
def lorentz_derivs(yvec, t, sigma, rho, beta):
Compute the the der... |
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