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12,800 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Anna KaRNNa
In this notebook, we'll build a character-wise RNN trained on Anna Karenina, one of my all-time favorite books. It'll be able to generate new text based on the text from the book... | Python Code:
import time
from collections import namedtuple
import numpy as np
import tensorflow as tf
Explanation: Anna KaRNNa
In this notebook, we'll build a character-wise RNN trained on Anna Karenina, one of my all-time favorite books. It'll be able to generate new text based on the text from the book.
This network... |
12,801 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Dynamical systems
A (discrete time) dynamical system describes the evolution of the state of a system and
the observations that can be obtained from the state. The general form is
\begin{eqn... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pylab as plt
N = 100
T = 100
a = 0.9
xm = 0.9
sP = np.sqrt(0.001)
sR = np.sqrt(0.01)
x1 = np.zeros(N)
x2 = np.zeros(N)
y = np.zeros(N)
for i in range(N):
if i==0:
x1[0] = xm
x2[0] = 0
else:
x1[i] = xm + a*x1[i-1] + np.r... |
12,802 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting
Introduction
This tutorial describes skrf's plotting features. If you would like to use skrf's matplotlib interface with skrf styling, start with this
Step1: Plotting Methods
Plot... | Python Code:
%matplotlib inline
import skrf as rf
rf.stylely()
Explanation: Plotting
Introduction
This tutorial describes skrf's plotting features. If you would like to use skrf's matplotlib interface with skrf styling, start with this
End of explanation
from skrf import Network
ring_slot = Network('data/ring slot.s2p... |
12,803 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time-frequency representations on topographies for MEG sensors
Both average power and intertrial coherence are displayed.
Step1: Set parameters
Step2: Calculate power and intertrial cohere... | Python Code:
# Authors: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Denis Engemann <denis.engemann@gmail.com>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne import io
from mne.time_frequency import tfr_morlet
from mne.datasets import somato... |
12,804 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Classification & How To "Frame Problems" for a Neural Network
by Andrew Trask
Twitter
Step1: Note
Step2: Lesson
Step3: Project 1
Step4: We'll create three Counter objects, one ... | Python Code:
def pretty_print_review_and_label(i):
print(labels[i] + "\t:\t" + reviews[i][:80] + "...")
g = open('reviews.txt','r') # What we know!
reviews = list(map(lambda x:x[:-1],g.readlines()))
g.close()
g = open('labels.txt','r') # What we WANT to know!
labels = list(map(lambda x:x[:-1].upper(),g.readlines())... |
12,805 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plot Type Selector
Example showing how to construct a dropdown widget that can be used to select a plot type. Here a dictionary must be used for the plot type options.
Step1: Load cube.
St... | Python Code:
import ipywidgets
import IPython.display
import iris
import numpy as np
import iris.quickplot as iplt
import matplotlib.pyplot as plt
Explanation: Plot Type Selector
Example showing how to construct a dropdown widget that can be used to select a plot type. Here a dictionary must be used for the plot type ... |
12,806 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bonus Material
Step1: Convert to list of words
Step2: Slower version without translate
Step3: Using a regular dictionary
Step4: Using a default dictionary
Step5: Using a Counter
Step6: ... | Python Code:
text = ''''Twas brillig, and the slithy toves
Did gyre and gimble in the wabe;
All mimsy were the borogoves,
And the mome raths outgrabe.
'Beware the Jabberwock, my son!
The jaws that bite, the claws that catch!
Beware the Jubjub bird, and shun
The frumious Bandersnat... |
12,807 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Solutions
Problem 1
Implement the Min-Max scaling function ($X'=a+{\frac {\left(X-X_{\min }\right)\left(b-a\right)}{X_{\max }-X_{\min }}}$) with the parameters
Step2: Problem 2
Use t... | Python Code:
# Problem 1 - Implement Min-Max scaling for greyscale image data
def normalize_greyscale(image_data):
Normalize the image data with Min-Max scaling to a range of [0.1, 0.9]
:param image_data: The image data to be normalized
:return: Normalized image data
a = 0.1
b = 0.9
gr... |
12,808 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Optimization of Degree Distributions on the BEC
This code is provided as supplementary material of the lecture Channel Coding 2 - Advanced Methods.
This code illustrates
* Using linear progr... | Python Code:
import cvxpy as cp
import numpy as np
import matplotlib.pyplot as plot
from ipywidgets import interactive
import ipywidgets as widgets
import math
%matplotlib inline
Explanation: Optimization of Degree Distributions on the BEC
This code is provided as supplementary material of the lecture Channel Coding ... |
12,809 | 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', 'nims-kma', 'sandbox-2', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: NIMS-KMA
Source ID: SANDBOX-2
Topic: Aerosol
Sub-Topics: Transport, E... |
12,810 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
eICU Collaborative Research Database
Notebook 3
Step2: 2. Display a list of tables
Step4: 3. Selecting a single patient stay
3.1. The patient table
The patient table includes general infor... | Python Code:
# Import libraries
import pandas as pd
import matplotlib.pyplot as plt
import psycopg2
import os
# Plot settings
%matplotlib inline
plt.style.use('ggplot')
fontsize = 20 # size for x and y ticks
plt.rcParams['legend.fontsize'] = fontsize
plt.rcParams.update({'font.size': fontsize})
# Connect to the databas... |
12,811 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This Notebook illustrates the usage of the OpenMC Python API's generic eigenvalue search capability. In this Notebook, we will do a critical boron concentration search of a typical PWR pin ... | Python Code:
# Initialize third-party libraries and the OpenMC Python API
import matplotlib.pyplot as plt
import numpy as np
import openmc
import openmc.model
%matplotlib inline
Explanation: This Notebook illustrates the usage of the OpenMC Python API's generic eigenvalue search capability. In this Notebook, we will d... |
12,812 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Setting the EEG reference
This tutorial describes how to set or change the EEG reference in MNE-Python.
As usual we'll start by importing the modules we need, loading some
example data <s... | Python Code:
import os
import mne
sample_data_folder = mne.datasets.sample.data_path()
sample_data_raw_file = os.path.join(sample_data_folder, 'MEG', 'sample',
'sample_audvis_raw.fif')
raw = mne.io.read_raw_fif(sample_data_raw_file, verbose=False)
raw.crop(tmax=60).load_data()
raw.pi... |
12,813 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis of Movie Reviews
This tutorial will guide you through the implementation of a recurrent neural network to analyze movie reviews on IMDB and decide if they are positive or ... | Python Code:
import pickle as pkl
data = pkl.load(open('data/imdb_data.pkl', 'r'))
Explanation: Sentiment Analysis of Movie Reviews
This tutorial will guide you through the implementation of a recurrent neural network to analyze movie reviews on IMDB and decide if they are positive or negative reviews.
The IMDB dataset... |
12,814 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Análisis de los datos obtenidos
Uso de ipython para el análsis y muestra de los datos obtenidos durante la producción.Se implementa un regulador experto. Los datos analizados son del día 13 ... | Python Code:
#Importamos las librerías utilizadas
import numpy as np
import pandas as pd
import seaborn as sns
#Mostramos las versiones usadas de cada librerías
print ("Numpy v{}".format(np.__version__))
print ("Pandas v{}".format(pd.__version__))
print ("Seaborn v{}".format(sns.__version__))
#Abrimos el fichero csv co... |
12,815 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Remote Interactive Task Manager LSASS Dump
Metadata
| | |
|
Step1: Download & Process Mordor Dataset
Step2: Analytic I
Look for taskmgr creating files which name conta... | Python Code:
from openhunt.mordorutils import *
spark = get_spark()
Explanation: Remote Interactive Task Manager LSASS Dump
Metadata
| | |
|:------------------|:---|
| collaborators | ['@Cyb3rWard0g', '@Cyb3rPandaH'] |
| creation date | 2019/10/30 |
| modification date | 2020/09/20 |
| play... |
12,816 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Importing and Processing CO2 Respiration Data from GC-MS
This script will convert output from the GC-MS from multiple sampling timepoints into a table. It can also calculate the mols C based... | Python Code:
## Provide the directory the contains subdirectories with timepoints
# example: '/home/roli/PROJECT/ which would contain sub-directories corresponding to timepoints T1, T2, T3 ... that containing the text output from the GC-MS
directory = '/home/roli/scripts/gcms/example_data/'
## Name the output for GC-MS... |
12,817 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Emojify!
Welcome to the second assignment of Week 2. You are going to use word vector representations to build an Emojifier.
Have you ever wanted to make your text messages more expressive?... | Python Code:
import numpy as np
from emo_utils import *
import emoji
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: Emojify!
Welcome to the second assignment of Week 2. You are going to use word vector representations to build an Emojifier.
Have you ever wanted to make your text messages more expressi... |
12,818 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Access-lists and firewall rules
This category of questions allows you to analyze the behavior of access
control lists and firewall rules. It also allows you to comprehensively
validate (aka ... | Python Code:
bf.set_network('generate_questions')
bf.set_snapshot('generate_questions')
Explanation: Access-lists and firewall rules
This category of questions allows you to analyze the behavior of access
control lists and firewall rules. It also allows you to comprehensively
validate (aka verification) that some traff... |
12,819 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Publication ready figures with matplotlib and Jupyter notebook
A very convenient workflow to analyze data and create figures that can be used in various ways for publication is to use the IP... | Python Code:
%matplotlib inline
import seaborn as snb
import numpy as np
import matplotlib.pyplot as plt
Explanation: Publication ready figures with matplotlib and Jupyter notebook
A very convenient workflow to analyze data and create figures that can be used in various ways for publication is to use the IPython Notebo... |
12,820 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kalman Filters
By Evgenia "Jenny" Nitishinskaya, Dr. Aidan O'Mahony, and Delaney Granizo-Mackenzie. Algorithms by David Edwards.
Kalman Filter Beta Estimation Example from Dr. Aidan O'Mahony... | Python Code:
%pylab inline
# Import a Kalman filter and other useful libraries
from pykalman import KalmanFilter
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from scipy import poly1d
Explanation: Kalman Filters
By Evgenia "Jenny" Nitishinskaya, Dr. Aidan O'Mahony, and Delaney Granizo-Mackenzie... |
12,821 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convolutional Cubic Splines
$C^2$-continuous cubic splines through evenly spaced data points can be created by convolving the data points with a $C^2$-continuous piecewise cubic kernel, char... | Python Code:
import math
#given an array of Y values at consecutive integral x abscissas,
#return array of corresponding derivatives to make a natural cubic spline
def naturalSpline(ys):
vs = [0.0] * len(ys)
if (len(ys) < 2):
return vs
DECAY = math.sqrt(3)-2;
endi = len(ys)-1
# make con... |
12,822 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning Engineer Nanodegree
Introduction and Foundations
Project 0
Step1: From a sample of the RMS Titanic data, we can see the various features present for each passenger on the s... | Python Code:
import numpy as np
import pandas as pd
# RMS Titanic data visualization code
from titanic_visualizations import survival_stats
from IPython.display import display
%matplotlib inline
# Load the dataset
in_file = 'titanic_data.csv'
full_data = pd.read_csv(in_file)
# Print the first few entries of the RMS Ti... |
12,823 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pandas
Sometimes you want a spreadsheet.
Starting point
Step1: Write a piece of code that prints the number 5, taken from some_dict.
Step2: A pandas dataframe is a dictionary of dictiona... | Python Code:
some_dict = {"x":{"a":1,"b":2,"c":3},
"y":{"a":4,"b":5,"c":6}}
Explanation: Pandas
Sometimes you want a spreadsheet.
Starting point
End of explanation
# Answer
some_dict["y"]["b"]
Explanation: Write a piece of code that prints the number 5, taken from some_dict.
End of explanation
import pan... |
12,824 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
20/10
Tipos de datos compuestos. Estructuras de control repetitivas.
Índices y slices
Diccionarios como acumuladores/contadores
Listas
Step1: Es fácil saber si un número está en la lista o... | Python Code:
lista_de_numeros = [1, 6, 3, 9, 5, 2]
print lista_de_numeros
print type(lista_de_numeros)
Explanation: 20/10
Tipos de datos compuestos. Estructuras de control repetitivas.
Índices y slices
Diccionarios como acumuladores/contadores
Listas
End of explanation
print 'El %s esta en %s?: %s' % (5, lista_de_nume... |
12,825 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Testing the back normalscore transformation
Step1: Getting the data ready for work
If the data is in GSLIB format you can use the function gslib.read_gslib_file(filename) to import the data... | Python Code:
#general imports
import matplotlib.pyplot as plt
import pygslib
from matplotlib.patches import Ellipse
import numpy as np
import pandas as pd
#make the plots inline
%matplotlib inline
Explanation: Testing the back normalscore transformation
End of explanation
#get the data in gslib format into a p... |
12,826 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cross-validation
In the machine learning examples, we have already shown the importance of split training and splitting data. However, a rough trial is not enough. Because if we randomly ass... | Python Code:
from sklearn.datasets import load_iris
from sklearn.cross_validation import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn import metrics
# read in the iris data
iris = load_iris()
# create X (features) and y (response)
X = iris.data
y = iris.target
# use train/test split ... |
12,827 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Comparing SDO/AIA Response Functions
Step1: Wavelength Response
First, load the SSW results into some convenient data structure.
Step2: Run the SunPy calculation.
Step3: Plot the results ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import sunpy.instr.aia
%matplotlib inline
Explanation: Comparing SDO/AIA Response Functions: SSW and SunPy
This notebook runs comparisons between the results of SSW and SunPy in calculating the wavelength and temperature response functions of the AIA instr... |
12,828 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting Started
<a name='contents'></a>
Contents
<a href='#magic'>The <tt>matmodlab</tt> namespace</a>
<a href='#model.def'>Defining a Model</a>
<a href='#model.def.mat'>Material Model Defin... | Python Code:
%pylab inline
from matmodlab2 import *
Explanation: Getting Started
<a name='contents'></a>
Contents
<a href='#magic'>The <tt>matmodlab</tt> namespace</a>
<a href='#model.def'>Defining a Model</a>
<a href='#model.def.mat'>Material Model Definition</a>
<a href='#model.def.step'>Step Definitions</a>
<a href=... |
12,829 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Linear SVC Sklearn - Training a Linear SVM Classification Model
| Python Code::
from sklearn.svm import SVC
from sklearn.metrics import classification_report
# create a linear SVC model with balanced class weights
model = SVC(C=1, kernel='linear', class_weight='balanced')
# fit model
model.fit(X_train, y_train)
# make predictions on test data
y_pred = model.predict(X_test)
# create a... |
12,830 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Analysis using Pandas
Pandas has become the defacto package for data analysis. In this workshop, we are going to use the basics of pandas to analyze the interests of today's group. We a... | Python Code:
import meetup.api
import pandas as pd
from IPython.display import Image, display, HTML
from itertools import combinations
Explanation: Data Analysis using Pandas
Pandas has become the defacto package for data analysis. In this workshop, we are going to use the basics of pandas to analyze the interests of t... |
12,831 | 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="#Lists" data-toc-modified-id="Lists-1"><span class="toc-item-num">1 </span>Lists</a></div><div class="lev2 toc-item"><a hr... | Python Code:
final = "It is with a heavy heart that I take up my pen to write these the last words in which I shall ever record the singular gifts by which my friend Mr. Sherlock Holmes was distinguished."
final = final.replace(".", "")
final = final.split(" ")
final
type(final)
Explanation: Table of Contents
<p><div c... |
12,832 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
First, I made a mistake naming the data set! It's 2015 data, not 2014 data. But yes, still use 311-2014.csv. You can rename it.
Importing and preparing your data
Import your data, but only t... | Python Code:
import datetime
import datetime as dt
dt.datetime.strptime('07/06/2015 10:58:27 AM', '%m/%d/%Y %I:%M:%S %p')
#datetime.datetime(2015, 7, 6, 0, 0)
parser = lambda date: pd.datetime.strptime(date, '%m/%d/%Y %H:%M:%S')
df = pd.read_csv("311-2015.csv", low_memory=False, parse_dates=[1], dtype=str , nrows=20000... |
12,833 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Facies classification using Random Forest
Contest entry by <a href=\"https
Step1: A complete description of the dataset is given in the Original contest notebook by Brendon Hall, Enthought... | Python Code:
###### Importing all used packages
%matplotlib inline
import warnings
warnings.filterwarnings('ignore')
import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.colors as colors
from mpl_toolkits.axes_grid1 import make_axes_locatable
import seaborn a... |
12,834 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to scikit-learn
Classification of Handwritten Digits the task is to predict, given an image, which digit it represents. We are given samples of each of the 10 possible classes (... | Python Code:
from sklearn import datasets
digits = datasets.load_digits()
%pylab inline
digits.data
digits.data.shape # n_samples, n_features
Explanation: Introduction to scikit-learn
Classification of Handwritten Digits the task is to predict, given an image, which digit it represents. We are given samples of each of... |
12,835 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Take the set of pings, make sure we have actual clientIds and remove duplicate pings.
Step2: We're going to dump each event from the pings. Do a little empty data sanitization so we don't g... | Python Code:
def dedupe_pings(rdd):
return rdd.filter(lambda p: p["meta/clientId"] is not None)\
.map(lambda p: (p["meta/documentId"], p))\
.reduceByKey(lambda x, y: x)\
.map(lambda x: x[1])
Explanation: Take the set of pings, make sure we have actual clientIds and remove d... |
12,836 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Science Demo
Step1: And now we create a HiveContext to enable Spark to access data from HIVE
Step2: Let's take a look at the dataset - first 5 rows
Step3: Exploring the Dataset
What ... | Python Code:
# Set up Spark Context
from pyspark import SparkContext, SparkConf
SparkContext.setSystemProperty('spark.executor.memory', '4g')
conf = SparkConf()
conf.set('spark.sql.autoBroadcastJoinThreshold', 200*1024*1024) # 200MB for map-side joins
conf.set('spark.executor.instances', 12)
sc = SparkContext('yarn-c... |
12,837 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The dataset
The dataset is the mnist digits which is a common toy data set for testing machine learning methods on images. This is a subset of the mnist set which have also been shrunked in ... | Python Code:
data = loadmat('small_mnist.mat')
# Training data (images, 0-9, even-odd)
# Images are stored in a (batch, x, y) array
# Labels are integers
train_im = data['train_im']
train_y = data['train_y'].ravel()
train_eo = data['train_eo'].ravel()
# Validation data (images, 0-9, even-odd)
# Same format as training ... |
12,838 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Measuring the J/$\psi$ Meson Mass
This notebook will walk you through a simplified measurement of the mass of the J/$\psi$ meson.
We will use data taken by the CMS experiment hosted on CERN'... | Python Code:
# Required imports and setup
import os
import numpy as np
from rootpy.plotting import Hist, Canvas, set_style, get_style
from rootpy import asrootpy, log
from root_numpy import root2array, fill_hist
from ROOT import (RooFit, RooRealVar, RooDataHist, RooArgList,
RooVoigtian, RooAddPdf, Roo... |
12,839 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Lecture 7
Step1: this matrix has $\mathcal{O}(1)$ elements in a row, therefore it is sparse.
Finite elements method is also likely to give you a system with a sparse matrix.
How to store a ... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
import scipy as sp
import matplotlib.cm as cm
%matplotlib inline
N = 3
B = np.diag(2*np.ones(N)) + np.diag((-1)*np.ones(N-1),k=-1)+ np.diag((-1)*np.ones(N-1),k = 1)
Id = np.diag(np.ones(N));
# Assembling a 3D operator:
A = np.kron(Id,np.kron(Id,B)) + np.k... |
12,840 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plotting topographic maps of evoked data
Load evoked data and plot topomaps for selected time points using multiple
additional options.
Step1: Basic plot_topomap options
We plot evoked topo... | Python Code:
# Authors: Christian Brodbeck <christianbrodbeck@nyu.edu>
# Tal Linzen <linzen@nyu.edu>
# Denis A. Engeman <denis.engemann@gmail.com>
# Mikołaj Magnuski <mmagnuski@swps.edu.pl>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
from mne.datasets import... |
12,841 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">TensorFlow Neural Network Lab</h1>
<img src="image/notmnist.png">
In this lab, you'll use all the tools you learned from Introduction to TensorFlow to label images of Engl... | Python Code:
import hashlib
import os
import pickle
from urllib.request import urlretrieve
import numpy as np
from PIL import Image
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import LabelBinarizer
from sklearn.utils import resample
from tqdm import tqdm
from zipfile import ZipFile
p... |
12,842 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This is a demo notebook of some of the features of IEtools.py.
IEtools includes tools to read FRED economic data
https
Step1: Read in the files
Step2: Here's a plot of nominal GDP
Step3: ... | Python Code:
import numpy as np
import IEtools
import pylab as pl
%pylab inline
Explanation: This is a demo notebook of some of the features of IEtools.py.
IEtools includes tools to read FRED economic data
https://fred.stlouisfed.org/
in either csv or xls formats. IEtools also includes tools for
fitting information equ... |
12,843 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2.1.1 Huberized Hinge loss
Plot on a same plot, with different colors, the misclassification error loss, the (regular) hinge loss, and the huberized hinge loss.
Step1: Explain how the hube... | Python Code:
%matplotlib inline
import matplotlib
import numpy as np
import matplotlib.pyplot as plt
from sklearn import preprocessing
from sklearn.datasets import make_blobs
from sklearn.svm import LinearSVC
x = np.linspace(-2.0, 2.0, num=100)
def huberizedHingeLoss(x, h):
if x > 1+h:
return 0
elif abs... |
12,844 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Text classification using Neural Networks
The goal of this notebook is to learn to use Neural Networks for text classification.
In this notebook, we will
Step1: Here are all the possible cl... | Python Code:
import numpy as np
from sklearn.datasets import fetch_20newsgroups
newsgroups_train = fetch_20newsgroups(subset='train')
newsgroups_test = fetch_20newsgroups(subset='test')
sample_idx = 1000
print(newsgroups_train["data"][sample_idx])
target_names = newsgroups_train["target_names"]
target_id = newsgroups_t... |
12,845 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Machine Learning Engineer Nanodegree
Model Evaluation & Validation
Project 1
Step1: Data Exploration
In this first section of this project, you will make a cursory investigation about the B... | Python Code:
# Import libraries necessary for this project
import numpy as np
import pandas as pd
import visuals as vs # Supplementary code
from sklearn.cross_validation import ShuffleSplit
# Pretty display for notebooks
%matplotlib inline
# Load the Boston housing dataset
data = pd.read_csv('housing.csv')
prices = dat... |
12,846 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Trace Analysis Examples
Idle States Residency Analysis
This notebook shows the features provided by the idle state analysis module. It will be necessary to collect the following events
Step1... | Python Code:
import logging
from conf import LisaLogging
LisaLogging.setup()
%matplotlib inline
import os
# Support to access the remote target
from env import TestEnv
# Support to access cpuidle information from the target
from devlib import *
# Support to configure and run RTApp based workloads
from wlgen import RTA,... |
12,847 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Neural Networks
Theano
Python library that provides efficient (low-level) tools for working with Neural Networks
In particular
Step1: Inspecting the data
Let's load some data
Step4: a... | Python Code:
from __future__ import absolute_import
from __future__ import print_function
from ipywidgets import interact, interactive, widgets
import numpy as np
np.random.seed(1337) # for reproducibility
Explanation: Deep Neural Networks
Theano
Python library that provides efficient (low-level) tools for working wit... |
12,848 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Feature Engineering
Learning Objectives
* Improve the accuracy of a model by using feature engineering
* Understand there's two places to do feature engineering in Tensor... | Python Code:
import tensorflow as tf
import numpy as np
import shutil
print(tf.__version__)
Explanation: Introduction to Feature Engineering
Learning Objectives
* Improve the accuracy of a model by using feature engineering
* Understand there's two places to do feature engineering in Tensorflow
1. Using the tf.... |
12,849 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
7 Clustering
Goal
Step1: Efficiency
The algorithm is $O(n^3) = \sum_{i=n}^{2} C_n^2$, since it computes the distances between each pair of clusters in iteration.
Optimize
Step2: 7.3.2 Init... | Python Code:
# Example 7.2
logger.setLevel('WARN')
points = np.array([
[4, 10],
[7, 10],
[4, 8],
[6, 8],
[3, 4],
[10, 5],
[12, 6],
... |
12,850 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook shows how to use an index file.<br/>
This example uses the index file from the Mediterranean Sea region (INSITU_MED_NRT_OBSERVATIONS_013_035) corresponding to the latest data.<... | Python Code:
indexfile = "./datafiles/index_latest.txt"
Explanation: This notebook shows how to use an index file.<br/>
This example uses the index file from the Mediterranean Sea region (INSITU_MED_NRT_OBSERVATIONS_013_035) corresponding to the latest data.<br/>
If you download the same file, the results will be sligh... |
12,851 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Product SVD in Python
In this NoteBook, the reader will find code to load GeoTiff files, single- or multi-band, from HDFS. It reads the GeoTiffs as a ByteArrays and then stores the GeoTiffs ... | Python Code:
#Add all dependencies to PYTHON_PATH
import sys
sys.path.append("/usr/lib/spark/python")
sys.path.append("/usr/lib/spark/python/lib/py4j-0.10.4-src.zip")
sys.path.append("/usr/lib/python3/dist-packages")
sys.path.append("/data/local/jupyterhub/modules/python")
#Define environment variables
import os
os.env... |
12,852 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using the trained weights in an ensemble of neurons
On the function points branch of nengo
On the vision branch of nengo_extras
Step1: Load the MNIST database
Step2: Each digit is represen... | Python Code:
import nengo
import numpy as np
import cPickle
from nengo_extras.data import load_mnist
from nengo_extras.vision import Gabor, Mask
from matplotlib import pylab
import matplotlib.pyplot as plt
import matplotlib.animation as animation
Explanation: Using the trained weights in an ensemble of neurons
On the f... |
12,853 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Author
Step1: Simulated FastQ data
Installation
Step2: Creating the BAM (mapping) and BED files
Step3: This uses bwa and samtools behind the scene. Then, we will convert the resulting BAM... | Python Code:
!sequana_coverage --download-reference FN433596
Explanation: Author: Thomas Cokelaer
Jan 2018
Local time execution: about 10 minutes
In this notebook, we will simulate fastq reads and inject CNVs. We will then look at the sensitivity (proportion of true positive by the sum of positives) of sequana_coverag... |
12,854 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Advanced
Step3: Let's also combine our plotting code into a cohesive function
Step4: Now we can tie our plot function, plot_planck, to the interact function from ipywidgets | Python Code:
# Import numpy and alias to "np"
import numpy as np
# Import and alias to "plt"
import matplotlib.pyplot as plt
def planck(wavelength, temp):
Return the emitted radiation from a blackbody of a given temp and wavelength
Args:
wavelength (float): wavelength (m)
temp (float): tem... |
12,855 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TOC Thematic Report - February 2019 (Part 1
Step2: 1.2. Finland
Jussi has supplied an entirely new dataset for all Finnish stations covering the period from 1990 to 2017. This supersedes th... | Python Code:
## Switch TOC/DOC pre-March 1995 to method with correction factor of 1.28
#with eng.begin() as conn:
# sql = ("UPDATE resa2.water_chemistry_values2 "
# "SET method_id = 10823 "
# "WHERE sample_id IN ( "
# " SELECT water_sample_id "
# " FROM resa2.water_samples ... |
12,856 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Get information for all stations in list and write out to JSON file
Step1: Optional | Python Code:
OUTFN = "AK_NCDC_FirstOrderStations.json"
SAVEDATA = False
stationdata = []
for station in all_stations:
path = os.path.join(endpoint_stations, "GHCND:{}".format(station))
fullbase = requests.compat.urljoin(baseurl, path)
r = requests.get(
fullbase,
headers=custom_headers,
... |
12,857 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
$$\begin{align}\Omega &= [0, 1]^2\
\Gamma_D &= \partial\Omega\end{align}$$
Step1: $$\begin{align}\kappa(x; \mu) & | Python Code:
g = grid.make_cube_grid__2d_simplex_aluconform(lower_left=[0, 0], upper_right=[1, 1], num_elements=[4, 4], num_refinements=2, overlap_size=[0, 0])
#g.visualize('grid')
Explanation: $$\begin{align}\Omega &= [0, 1]^2\
\Gamma_D &= \partial\Omega\end{align}$$
End of explanation
#bump = functions.make_expressio... |
12,858 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Contextual Bandits with TF-agents
Learning Objectives
Learn to load a dataset in BigQuery and connect to it using TensorFlow IO
Learn how to transform a classification dataset into a context... | Python Code:
pip freeze | grep tf_agents || pip install -q tf_agents==0.11.0
Explanation: Contextual Bandits with TF-agents
Learning Objectives
Learn to load a dataset in BigQuery and connect to it using TensorFlow IO
Learn how to transform a classification dataset into a contextual bandit problem
Learn how to stream a... |
12,859 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Sklearn Gradient Boosting Regressor - Training a Regression Model
| Python Code::
from sklearn.ensemble import GradientBoostingRegressor
from sklearn.metrics import mean_squared_error, mean_absolute_error, max_error, explained_variance_score, mean_absolute_percentage_error
# initialise & fit Gradient Boosting Regressor
model = GradientBoostingRegressor(loss='squared_error',
... |
12,860 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
d3viz
Step1: Like Theano’s printing module, d3viz
requires graphviz binary to be available.
Overview
d3viz extends Theano’s printing module to interactively visualize compute graphs. Instea... | Python Code:
!pip install pydot-ng
Explanation: d3viz: Interactive visualization of Theano compute graphs
Requirements
d3viz requires the pydot
package. pydot-ng fork is better
maintained, and it works both in Python 2.x and 3.x. Install it with pip::
End of explanation
import theano as th
import theano.tensor as T
imp... |
12,861 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center>
<h1> ILI285 - Computación Científica I / INF285 - Computación Científica </h1>
<h2> Linear Systems of Equations </h2>
<h2> <a href="#acknowledgements"> [S]cientific [C]... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
Explanation: <center>
<h1> ILI285 - Computación Científica I / INF285 - Computación Científica </h1>
<h2> Linear Systems of Equations </h2>
<h2> <a href="#acknowledgements"> [S]cientific [C]omputing [T]eam </a> </h2>
<h2... |
12,862 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Python API to EasyForm
Step1: You can access the values from the form by treating it as an array indexed on the field names
Step2: The array works both ways, so you set default values on t... | Python Code:
from beakerx import *
f = EasyForm("Form and Run")
f.addTextField("first")
f['first'] = "First"
f.addTextField("last")
f['last'] = "Last"
f.addButton("Go!", tag="run")
f
Explanation: Python API to EasyForm
End of explanation
"Good morning " + f["first"] + " " + f["last"]
f['last'][::-1] + '...' + f['first'... |
12,863 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ordinary Differential Equations Exercise 3
Imports
Step1: Damped, driven nonlinear pendulum
The equations of motion for a simple pendulum of mass $m$, length $l$ are
Step4: Write a functio... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
from scipy.integrate import odeint
from IPython.html.widgets import interact, fixed
Explanation: Ordinary Differential Equations Exercise 3
Imports
End of explanation
g = 9.81 # m/s^2
l = 0.5 # length of pendul... |
12,864 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
SAP Credv2
The following subsections show a representation of the file format portions and how to generate them.
First we need to perform some setup to import the packet classes
Step1: Cred... | Python Code:
from pysap.SAPCredv2 import *
from IPython.display import display
Explanation: SAP Credv2
The following subsections show a representation of the file format portions and how to generate them.
First we need to perform some setup to import the packet classes:
End of explanation
with open("../../tests/data/cr... |
12,865 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Recommendation Methods
Step1: Recommendation Comparison
A more general framework for comparing different recommendation techniques
Evaluation DataSet
See notes in the creating_dataset_for_e... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns
sns.set_style('white')
%matplotlib inline
import sys
import os
sys.path.append('../')
os.getcwd()
import src
import src.recommendation
reload(src.recommendation)
from src.recommendation import *
Explanation: Recomm... |
12,866 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Implicit Georeferencing
This workbook sets explicit georeferences from implicit georeferencing through names of extents given in dataset titles or keywords.
A file sources.py needs to contai... | Python Code:
import ckanapi
from harvest_helpers import *
from secret import CKAN
ckan = ckanapi.RemoteCKAN(CKAN["dpaw-internal"]["url"], apikey=CKAN["dpaw-internal"]["key"])
print("Using CKAN {0}".format(ckan.address))
Explanation: Implicit Georeferencing
This workbook sets explicit georeferences from implicit georefe... |
12,867 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction To OANDA-System
Environment
Step1: Data Containers
Tick
Bar
Event Objects
market event
bar event
signal event
order event
fill event
Event Queue Object
Should be structured in ... | Python Code:
from api import*
myConfig = Config()
myConfig.view()
Explanation: Introduction To OANDA-System
Environment:
Python-Anaconda 2.7
pandas, json, requests
Config Class
Contains infomations that we need to connect to OANDA server and make requests.
End of explanation
q1 = EventQueue()
q2 = EventQueue()
q = {'mk... |
12,868 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Tutorial de especificação de histograma, caso discreto exato
O problema consiste em mapear os pixels de uma imagem dada para que o histograma da
imagem transformada seja um histograma especi... | 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
hout = np.concatenate((np.arange(128),np.aran... |
12,869 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
First, load up the data
First you're going to want to create a data frame from the dailybots.csv file which can be found in the data directory. You should be able to do this with the pd.rea... | Python Code:
data = pd.read_csv( '../../data/dailybots.csv' )
#Look at a summary of the data
data.describe()
data['botfam'].value_counts()
Explanation: First, load up the data
First you're going to want to create a data frame from the dailybots.csv file which can be found in the data directory. You should be able to d... |
12,870 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bolidozor FITS files time restorer
For use of this notebook you must have mounted space.astro.cz storage server to local filesystem. It is possible to do with sshfs
bash
sshfs <user>... | Python Code:
import os
import datetime
import numpy
import scipy.signal
from astropy.io import fits
import matplotlib.pyplot as plt
import matplotlib.dates as md
%matplotlib inline
paths = ['/home/roman/mnt/server-space/storage/bolidozor/ZVPP/ZVPP-R6/snapshots/2017/09/']
times = numpy.ndarray((0,2))
start_time = date... |
12,871 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Object Detection API Demo
<table align="left"><td>
<a target="_blank" href="https
Step1: Make sure you have pycocotools installed
Step2: Get tensorflow/models or cd to parent directory ... | Python Code:
!pip install -U --pre tensorflow=="2.*"
!pip install tf_slim
Explanation: Object Detection API Demo
<table align="left"><td>
<a target="_blank" href="https://colab.sandbox.google.com/github/tensorflow/models/blob/master/research/object_detection/colab_tutorials/colab_tutorials/object_detection_tutorial.... |
12,872 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Python
This tutorial was originally drawn from Scipy Lecture Notes by this list of contributors. I've continued to modify it as I use it.
This work is CC-BY. Author
Step1: A... | Python Code:
# open the source CSV file
csv = open("cars.csv")
# create a list with the column names. we assume the first row contiains them.
# we strip the carriage return (if there is one) from the line, then split values on the commas.
# Note: this uses a nifty python feature called 'list comprehension' to do it in ... |
12,873 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Scraping Reviews
This notebook shows how to use the scrape reviews from Indeed and Glassdoor. To visualize the ratings go to the Ratings notebook and to do topic modeling go to the Topic Mod... | Python Code:
# Search settings
KEYWORD_FILTER = "Data Scientist"
LOCATION_FILTER = "New York City, NY"
# Other settings
MAX_PAGES_COMPANIES = 500
MAX_PAGES_REVIEWS = 500
import os
import re
from datetime import datetime
from pymongo import MongoClient
import indeed
import glassdoor
import utils
# DB settings
client = M... |
12,874 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
INF-495, v0.01, Claudio Torres, ctorres@inf.utfsm.cl. DI-UTFSM
Textbook
Step1: First algorithm
Step2: Second algorithm
Step3: Third algorithm
Step4: 8.2 Stochastic predator-prey model | Python Code:
import numpy as np
import scipy.sparse.linalg as sp
import sympy as sym
from scipy.linalg import toeplitz
import ipywidgets as widgets
from ipywidgets import IntSlider
import matplotlib.pyplot as plt
%matplotlib inline
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatte... |
12,875 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Workshop 4 - Performance Metrics
In this workshop we study 2 performance metrics(Spread and Inter-Generational Distance) on GA optimizing the POM3 model.
Step2: To compute most measures, da... | Python Code:
%matplotlib inline
# All the imports
from __future__ import print_function, division
import pom3_ga, sys
import pickle
# TODO 1: Enter your unity ID here
__author__ = "dndesai"
Explanation: Workshop 4 - Performance Metrics
In this workshop we study 2 performance metrics(Spread and Inter-Generational Dista... |
12,876 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Module 1
Step2: Given the dataset, let's test our dataset by seeing some of the images and their corresponding labels. PyTorch provides us with a neat little function called make_gri... | Python Code:
import sys, os
import pickle
import torch
import torch.utils.data as data
import glob
from PIL import Image
import numpy as np
def unpickle(fname):
with open(fname, 'rb') as f:
Dict = pickle.load(f, encoding='bytes')
return Dict
def load_data(batch):
print ("Loading batch:{}".format... |
12,877 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Kalman Filter and your Matrix Class
Once you have a working matrix class, you can use the class to run a Kalman filter!
You will need to put your matrix class into the workspace
Step1: Vis... | Python Code:
%matplotlib inline
import pandas as pd
import math
import matplotlib.pyplot as plt
import matplotlib
import datagenerator
import matrix as m
matplotlib.rcParams.update({'font.size': 16})
# data_groundtruth() has the following inputs:
# Generates Data
# Input variables are:
# initial position meters
# initi... |
12,878 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
VirtualEATING
Andrew Lane, University of California, Berkeley
Overview
CRISPR-EATING is a molecular biology protocol to generate libraries of CRISPR guide RNAs. The use of this this approach... | Python Code:
import Bio
from Bio.Blast.Applications import NcbiblastnCommandline
from Bio import SeqIO
from Bio.Blast import NCBIXML
from Bio import Restriction
from Bio.Restriction import *
from Bio.Alphabet.IUPAC import IUPACAmbiguousDNA
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
import cPickle as ... |
12,879 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example Q3
Step1: Creating the Default Filter Pipeline
Step2: The PipelineManager is analogous to the ChannelLibrary insomuchas it provides the user with an interface to programmatically m... | Python Code:
from QGL import *
cl = ChannelLibrary(":memory:")
# Create five qubits and supporting hardware
for i in range(5):
q1 = cl.new_qubit(f"q{i}")
cl.new_APS2(f"BBNAPS2-{2*i+1}", address=f"192.168.5.{101+2*i}")
cl.new_APS2(f"BBNAPS2-{2*i+2}", address=f"192.168.5.{102+2*i}")
cl.new_X6(f"X6_{i}", ... |
12,880 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
colvolve given image uisng python or scipy
| Python Code::
from scipy.signal import convolve2d
import numpy as np
from scipy.stats import norm
import matplotlib.pyplot as plt
gray = np.mean(image, axis =2)
x = np.linspace(-6, 6 , 40)
fx = norm.pdf(x, loc= 0, scale =1)
filt = np.outer(fx, fx)
output = convolve2d(gray, filt)
plt.imshow(output)
|
12,881 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Language Translation
In this project, you’re going to take a peek into the realm of neural network machine translation. You’ll be training a sequence to sequence model on a dataset o... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
import problem_unittests as tests
source_path = 'data/small_vocab_en'
target_path = 'data/small_vocab_fr'
source_text = helper.load_data(source_path)
target_text = helper.load_data(target_path)
Explanation: Language Translation
In this project, you’re going ... |
12,882 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: 1. Write a function that returns the Pythagorean triplet (a, b, c) given any two of the arguments a, b or c.
For example, triplet(a=3, c=5) will return (3, 4, 5).
Step3: 2. The $n^\t... | Python Code:
import numpy as np
def triplet(a=None, b=None, c=None):
Returns the Pythagoraen tripler (a, b, c) given any two arguments.
Assumes but does not check that two named argumets are called.
Retruns None if no triplet possible with given arguments.
if a is None:
q, r = div... |
12,883 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Outline
Glossary
Positional Astronomy
Next
Step1: Import section specific modules | Python Code:
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
from IPython.display import HTML
HTML('../style/course.css') #apply general CSS
Explanation: Outline
Glossary
Positional Astronomy
Next: Equatorial Coordinates
Import standard modules:
End of explanation
from IPython.display import HTML... |
12,884 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Memory-efficient embeddings for recommendation systems
Author
Step1: Prepare the data
Download and process data
Step2: Create train and eval data splits
Step3: Define dataset metadata and... | Python Code:
import os
import math
from zipfile import ZipFile
from urllib.request import urlretrieve
import numpy as np
import pandas as pd
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
from tensorflow.keras.layers import StringLookup
import matplotlib.pyplot as plt
Explanati... |
12,885 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Introduction" data-toc-modified-id="Introduction-1"><span class="toc-item-nu... | Python Code:
debug_flag = False
Explanation: <h1>Table of Contents<span class="tocSkip"></span></h1>
<div class="toc"><ul class="toc-item"><li><span><a href="#Introduction" data-toc-modified-id="Introduction-1"><span class="toc-item-num">1 </span>Introduction</a></span></li><li><span><a href="#Setup" data-to... |
12,886 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
What is Serial Dependence?
In earlier lessons, we investigated properties of time series that were most easily modeled as time dependent properties, that is, with features we could derive di... | Python Code:
#$HIDE_INPUT$
import pandas as pd
# Federal Reserve dataset: https://www.kaggle.com/federalreserve/interest-rates
reserve = pd.read_csv(
"../input/ts-course-data/reserve.csv",
parse_dates={'Date': ['Year', 'Month', 'Day']},
index_col='Date',
)
y = reserve.loc[:, 'Unemployment Rate'].dropna().to... |
12,887 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
http
Step1: Complex
1-n correspondance
Step2: https | Python Code:
keyEN = ['red', 'yellow', 'green', 'blue', 'black']
keyFR1 = ['rouge', 'jaune', 'vert', 'bleu', 'noir']
keyFR2 = ['jaune', 'vert', 'bleu', 'noir', 'rouge']
keyDE = ['gelb', 'gruen', 'blau', 'schwartz', 'rot']
dataENFR = pd.DataFrame({'keyEN' : keyEN, 'keyFR' : keyFR1})
dataENFR
dataFRDE = pd.DataFrame({'ke... |
12,888 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
The input data
Here we use the (not publically available) data for Chicago, which has we believe accurate geocoding.
Step1: Just the south side
Step2: Covariance
For KDE applications, it i... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import matplotlib
import descartes
import os
import numpy as np
import descartes
import open_cp.sources.chicago as chicago
import open_cp.naive
import open_cp.geometry
import open_cp.plot
datadir = os.path.join("//media", "disk", "Data")
#datadir = os.path... |
12,889 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
In this blog post, I want to show you a graph-based way to split up a class into several independent ones. We take a small example class from Michael Feathers' book "Working eff... | Python Code:
%load_ext cypher
Explanation: Introduction
In this blog post, I want to show you a graph-based way to split up a class into several independent ones. We take a small example class from Michael Feathers' book "Working effectively with legacy code" and use Neo4j's Awesome Procedures On Cypher (APOC).
Hint: T... |
12,890 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Async optimization Loop
Tim Head, February 2017.
Step1: Bayesian optimization is used to tune parameters for walking robots or other experiments
that are not a simple (expensive) function c... | Python Code:
import numpy as np
np.random.seed(1234)
%matplotlib inline
import matplotlib.pyplot as plt
plt.set_cmap("viridis")
Explanation: Async optimization Loop
Tim Head, February 2017.
End of explanation
from skopt.learning import ExtraTreesRegressor
from skopt import Optimizer
noise_level = 0.1
# Our 1D toy probl... |
12,891 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Variational Auto Encoders
Reference
Step1: Fashion MNIST
Step2: Standard full-connected VAE model
Let's define a VAE model with fully connected MLPs for the encoder and decoder networks.
... | Python Code:
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
from tensorflow.keras.layers import Input, Dense, Lambda, Flatten, Reshape, Conv2D, Conv2DTranspose
from tensorflow.keras.models import Model
from tensorflow.keras import metrics
from tensorflow.keras.da... |
12,892 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Build simple models to predict pulsar candidates
In this notebook we will look at building machine learning models to predict Pulsar Candidate. The data comes from Rob Lyon at Manchester. Th... | Python Code:
# For numerical stuff
import pandas as pd
# Plotting
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
%matplotlib inline
plt.rcParams['figure.figsize'] = (7.0, 7.0)
# Some preprocessing utilities
from sklearn.cross_validation import train_test_split # Data splitting
from sklearn.util... |
12,893 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
201 - Engineering Text Features Using mmlspark Modules and Spark SQL
Again, try to predict Amazon book ratings greater than 3 out of 5, this time using
the TextFeaturizer module which is a c... | Python Code:
import pandas as pd
import mmlspark
from pyspark.sql.types import IntegerType, StringType, StructType, StructField
dataFile = "BookReviewsFromAmazon10K.tsv"
textSchema = StructType([StructField("rating", IntegerType(), False),
StructField("text", StringType(), False)])
import os, u... |
12,894 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
version 1.0.2
+
Introduction to Machine Learning with Apache Spark
Predicting Movie Ratings
One of the most common uses of big data is to predict what users want. This allows Google to sh... | Python Code:
import sys
import os
from test_helper import Test
baseDir = os.path.join('data')
inputPath = os.path.join('cs100', 'lab4', 'small')
ratingsFilename = os.path.join(baseDir, inputPath, 'ratings.dat.gz')
moviesFilename = os.path.join(baseDir, inputPath, 'movies.dat')
Explanation: version 1.0.2
+
Introductio... |
12,895 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Logbook Blocking
An implementation of the network-based blocking mechanism
Step1: Graph Structured Pairwise Comparisons
By implementing a graph where person entity nodes are a tuple of (nam... | Python Code:
%matplotlib inline
import os
import sys
import random
import networkx as nx
## Paths from the file
PROJECT = os.path.join(os.getcwd(), "..")
FIXTURES = os.path.join(PROJECT, "fixtures")
DATASET = os.path.join(FIXTURES, 'activity.csv')
## Append the path for the logbook utilities
sys.path.append(PROJE... |
12,896 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Example for using the Pvlib model
The Pvlib model can be used to determine the feed-in of a photovoltaic module using the pvlib.
The pvlib is a python library for simulating the performance ... | Python Code:
from feedinlib import Photovoltaic
# suppress warnings
import warnings
warnings.filterwarnings("ignore")
Explanation: Example for using the Pvlib model
The Pvlib model can be used to determine the feed-in of a photovoltaic module using the pvlib.
The pvlib is a python library for simulating the performance... |
12,897 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Биномиальный критерий для доли
Step1: Shaken, not stirred
Джеймс Бонд говорит, что предпочитает мартини взболтанным, но не смешанным. Проведём слепой тест (blind test)
Step2: Односторонняя... | Python Code:
import numpy as np
from scipy import stats
%pylab inline
Explanation: Биномиальный критерий для доли
End of explanation
n = 16
F_H0 = stats.binom(n, 0.5)
x = np.linspace(0,16,17)
pylab.bar(x, F_H0.pmf(x), align = 'center')
xlim(-0.5, 16.5)
pylab.show()
Explanation: Shaken, not stirred
Джеймс Бонд говорит,... |
12,898 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Mit Datenanalysen Probleme in der Entwicklung aufzeigen
<small>Java User Group Hessen, Kassel, 25.04.2019</small>
<b>Markus Harrer</b>, Software Development Analyst
Twitter
Step1: Was haben... | Python Code:
import pandas as pd
log = pd.read_csv("../dataset/linux_blame_log.csv.gz")
log.head()
Explanation: Mit Datenanalysen Probleme in der Entwicklung aufzeigen
<small>Java User Group Hessen, Kassel, 25.04.2019</small>
<b>Markus Harrer</b>, Software Development Analyst
Twitter: @feststelltaste
Blog: feststelltas... |
12,899 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
OIQ Exam Question 2
Question from OIQ Technical Exam, obviously meant to be solved using moment distribution, but
here we see how easy it is using slope deflection instead. This version use... | Python Code:
from IPython import display
display.SVG('oiq-frame-1.svg')
Explanation: OIQ Exam Question 2
Question from OIQ Technical Exam, obviously meant to be solved using moment distribution, but
here we see how easy it is using slope deflection instead. This version users a newer version of 'sdutil'
that computes ... |
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