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3,200 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<center> Earth's Energy Budget </center>
<img src = 'https
Step1: Clear sky downward solar flux is considered to be equivalent to solar radiation after clouds
Step2: compare CIMIS (measure... | Python Code:
from IPython.display import HTML
HTML('''<script>
code_show=true;
function code_toggle() {
if (code_show){
$('div.input').hide();
} else {
$('div.input').show();
}
code_show = !code_show
}
$( document ).ready(code_toggle);
</script>
<form action="javascript:code_toggle()"><input type="submit" value... |
3,201 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Webscraping with Beautiful Soup
In this lesson we'll learn about various techniques to scrape data from websites. This lesson will include
Step1: 1. Using BeautifulSoup
1.1 Make a GET reque... | Python Code:
import requests # to make GET request
from bs4 import BeautifulSoup # to parse the HTML response
import time # to pause between calls
import csv # to write data to csv
import pandas # to see CSV
Explanation: Webscraping with Beautiful Soup
In this lesson we'll learn about various techniques to scrape ... |
3,202 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Importing and Exporting Data
Data can be imported into Google BigQuery from a CSV file stored within Google Cloud Storage, or it can be streamed directly into BigQuery from Python code.
Simi... | Python Code:
from google.datalab import Context
import google.datalab.bigquery as bq
import google.datalab.storage as storage
import pandas as pd
try:
from StringIO import StringIO
except ImportError:
from io import BytesIO as StringIO
Explanation: Importing and Exporting Data
Data can be imported into Google BigQu... |
3,203 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step6: Processing Multisentence Documents
Step8: Define markup_sentence
We are putting the functionality we went through in the previous two notebooks (BasicSentenceMarkup and BasicSentence... | Python Code:
import pyConTextNLP.pyConTextGraph as pyConText
import pyConTextNLP.itemData as itemData
from textblob import TextBlob
import networkx as nx
import pyConTextNLP.display.html as html
from IPython.display import display, HTML
reports = [
IMPRESSION: Evaluation limited by lack of IV contrast; however, no ... |
3,204 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examining the 100-year storm
From past analysis, we've seen that there have been 3 100-year storms in the last 46 years. This notebook takes a look at these 3 storms.
Step1: Storm 1 -> Aug... | Python Code:
from __future__ import absolute_import, division, print_function, unicode_literals
import numpy as np
from datetime import datetime, timedelta
import pandas as pd
import matplotlib.pyplot as plt
import operator
import seaborn as sns
%matplotlib inline
n_year_storms = pd.read_csv('data/n_year_storms_ohare_n... |
3,205 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cirq to Tensor Networks
Here we demonstrate turning circuits into tensor network representations of the circuit's unitary, final state vector, final density matrix, and final noisy density m... | Python Code:
import cirq
import numpy as np
import pandas as pd
from cirq.contrib.svg import SVGCircuit
import cirq.contrib.quimb as ccq
import quimb
import quimb.tensor as qtn
Explanation: Cirq to Tensor Networks
Here we demonstrate turning circuits into tensor network representations of the circuit's unitary, final s... |
3,206 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Stacks
Stacks are one of the basic, linear datastructures that have the characteristical 2 end points (here
Step1: Note that the addition and removal of a single item is a O(1) algorithm
St... | Python Code:
class Stack(object):
def __init__(self):
self.stack = []
def add(self, item):
self.stack.append(item)
def pop(self):
self.stack.pop()
def peek(self):
return self.stack[-1]
def size(self):
return len(self.stack)
Explanation: Sta... |
3,207 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An Introduction to Multi-fidelity Modeling in Emukit
Overview
A common issue encountered when applying machine learning to environmental sciences and engineering problems is the difficulty o... | Python Code:
# General imports
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import colors as mcolors
colors = dict(mcolors.BASE_COLORS, **mcolors.CSS4_COLORS)
%matplotlib inline
np.random.seed(20)
Explanation: An Introduction to Multi-fidelity Modeling in Emukit
Overview
A common issue encountered... |
3,208 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Resumen de estructuras de datos de Python
Tuplas, Listas, Sets, Diccionarios, Listas de comprehension, Funciones, Clases
Vamos a ver ejemplos de estrucutras de datos en Python
Tuplas
Son el ... | Python Code:
x = (1,2,3,0,2,1)
x
x = (0, 'Hola', (1,2))
x[1]
Explanation: Resumen de estructuras de datos de Python
Tuplas, Listas, Sets, Diccionarios, Listas de comprehension, Funciones, Clases
Vamos a ver ejemplos de estrucutras de datos en Python
Tuplas
Son el tipo mas simple de estr. puede almacenar en una misma va... |
3,209 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convolutional Autoencoder
Sticking with the MNIST dataset, let's improve our autoencoder's performance using convolutional layers. Again, loading modules and the data.
Step1: Network Archit... | Python Code:
%matplotlib inline
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets('MNIST_data', validation_size=0)
img = mnist.train.images[2]
plt.imshow(img.reshape((28, 28)), cmap='Greys_r')
Explanati... |
3,210 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 Google LLC.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: Simple Activation Atlas
This notebook uses Lucid to reproduce the results in Activation At... | Python Code:
# 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
# distribute... |
3,211 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook, we will work through a Bayes Net analysis using the GES algorithm with the TETRAD software (http
Step1: Load the data generated using the DCM forward model. In this model,... | Python Code:
import os,sys
import numpy
%matplotlib inline
import matplotlib.pyplot as plt
sys.path.insert(0,'../')
from utils.mkdesign import create_design_singlecondition
from nipy.modalities.fmri.hemodynamic_models import spm_hrf,compute_regressor
from utils.make_data import make_continuous_data
from utils.graph_uti... |
3,212 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data block API foundations
Step1: Jump_to lesson 11 video
Step2: Image ItemList
Previously we were reading in to RAM the whole MNIST dataset at once, loading it as a pickle file. We can't ... | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
#export
from exp.nb_07a import *
Explanation: Data block API foundations
End of explanation
datasets.URLs.IMAGENETTE_160
Explanation: Jump_to lesson 11 video
End of explanation
path = datasets.untar_data(datasets.URLs.IMAGENETTE_160)
path
Explanation: I... |
3,213 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PCA Analysis
Step1: Feature Selection
Step2: Logistic Regression
Step3: Naive Bayes
Step4: KNN
Step5: Random Forest
Step6: Decision Tree
Step7: SVC
Step8: Gradient Boosting
Step9: C... | Python Code:
# Build up the correlation mtrix
Z = X1
correlation_matrix = Z.corr()
#Eigenvectores & Eigenvalues
eig_vals, eig_vecs = np.linalg.eig(correlation_matrix)
sklearn_pca = PCA(n_components=len(Z.columns))
Y_sklearn = sklearn_pca.fit_transform(correlation_matrix)
#From the Scree plot.
plt.plot(eig_vals)
plt.sho... |
3,214 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interact Exercise 01
Import
Step1: Interact basics
Write a print_sum function that prints the sum of its arguments a and b.
Step2: Use the interact function to interact with the print_sum ... | Python Code:
%matplotlib inline
from matplotlib import pyplot as plt
import numpy as np
from IPython.html.widgets import interact, interactive, fixed
from IPython.display import display
Explanation: Interact Exercise 01
Import
End of explanation
def print_sum(a, b):
print(a + b)
Explanation: Interact basics
Write a... |
3,215 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PyBroMo 5. Two-state dynamics - Dynamic smFRET simulation
<small><i>
This notebook is part of <a href="http
Step1: Timestamps, detectors and particles for the two states
Step2: Simulation
... | Python Code:
from pathlib import Path
from textwrap import dedent, indent
import numpy as np
import tables
from scipy.stats import expon
import phconvert as phc
print('phconvert version:', phc.__version__)
SIM_PATH = 'data/'
filelist = list(Path(SIM_PATH).glob('smFRET_*_600s.hdf5'))
[f.name for f in filelist]
filename_... |
3,216 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img align="left" src="imgs/logo.jpg" width="50px" style="margin-right
Step1: We repeat our definition of the Spouse Candidate subclass, and load the test set
Step2: I. Training a SparseLo... | Python Code:
%load_ext autoreload
%autoreload 2
%matplotlib inline
import os
import numpy as np
# Connect to the database backend and initalize a Snorkel session
from lib.init import *
Explanation: <img align="left" src="imgs/logo.jpg" width="50px" style="margin-right:10px">
Snorkel Workshop: Extracting Spouse Relation... |
3,217 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Optimizing Real World Problems
In this workshop we will code up a model called POM3 and optimize it using the GA we developed in the first workshop.
POM3 is a software estimation mode... | Python Code:
%matplotlib inline
# All the imports
from __future__ import print_function, division
from math import *
import random
import sys
import matplotlib.pyplot as plt
# TODO 1: Enter your unity ID here
__author__ = "latimko"
class O:
Basic Class which
- Helps dynamic updates
- Pretty Pr... |
3,218 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
PRINCIPLE COMPONENT ANALYSIS
Authors
Ndèye Gagnessiry Ndiaye and Christin Seifert
License
This work is licensed under the Creative Commons Attribution 3.0 Unported License https
Step1: Th... | Python Code:
import pandas as pd
import numpy as np
import pylab as plt
import matplotlib.pyplot as plt
from sklearn.decomposition import PCA
Explanation: PRINCIPLE COMPONENT ANALYSIS
Authors
Ndèye Gagnessiry Ndiaye and Christin Seifert
License
This work is licensed under the Creative Commons Attribution 3.0 Unported... |
3,219 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Optimizing Python Code
Step1: Pairwise Distance Estimation
Step2: The timiing for the results in Jake's post (2013) and the results from this post (2017) are summarized below.
Step3: The ... | Python Code:
import numpy as np
import numba
import cython
%load_ext cython
import pandas as pd
numba.__version__, cython.__version__, np.__version__
Explanation: Optimizing Python Code: Numba vs Cython
Goutham Balaraman
I came across an old post by jakevdp on Numba vs Cython. I thought I will revisit this topic becau... |
3,220 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Rotate Array
Step1: Simple Solution
The simplest solution splits the array at the point to rotate, and constructs a new array using the two parts.
Step2: This solution has both time and sp... | Python Code:
import sys; sys.path.append('../..')
from puzzles import leet_puzzle
leet_puzzle('rotate-array')
n, k = 7, 4
example_array = list(range(n))
example_array
Explanation: Rotate Array
End of explanation
def rotate_simple(input_array, order):
order %= len(input_array)
return input_array[order:] + input_... |
3,221 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
AveragePooling2D
[pooling.AveragePooling2D.0] input 6x6x3, pool_size=(2, 2), strides=None, padding='valid', data_format='channels_last'
Step1: [pooling.AveragePooling2D.1] input 6x6x3, pool... | Python Code:
data_in_shape = (6, 6, 3)
L = AveragePooling2D(pool_size=(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(270)
da... |
3,222 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step4: Demo - Storing information in EEX
Step8: Storing force field information
So far, only the topology and coordinates of the system are specified, and we are not able to calculate an en... | Python Code:
import eex
import os
import pandas as pd
import numpy as np
# Create empty data layer
dl = eex.datalayer.DataLayer("butane", backend="Memory")
dl.summary()
First, we add atoms to the system. Atoms have associated metadata. The possible atom metadata is listed here.
dl.list_valid_atom_properties()
TOPOLOGY:... |
3,223 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise 06
Data preparation and model evaluation exercise with Titanic data
We'll be working with a dataset from Kaggle's Titanic competition
Step1: Exercise 6.1
Impute the missing values ... | Python Code:
import pandas as pd
url = 'https://raw.githubusercontent.com/justmarkham/DAT8/master/data/titanic.csv'
titanic = pd.read_csv(url, index_col='PassengerId')
titanic.head()
Explanation: Exercise 06
Data preparation and model evaluation exercise with Titanic data
We'll be working with a dataset from Kaggle's T... |
3,224 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: <i class="fa fa-diamond"></i> Primero pimpea tu libreta!
Step2: Un poco de estadística
Step3: Hacemos dos listas, la primera contendrá las edades de los chavos de clubes de ciencia ... | Python Code:
from IPython.core.display import HTML
import os
def css_styling():
Load default custom.css file from ipython profile
base = os.getcwd()
styles = "<style>\n%s\n</style>" % (open(os.path.join(base,'files/custom.css'),'r').read())
return HTML(styles)
css_styling()
Explanation: <i class="fa fa-... |
3,225 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Spherical Harmonic Normalizations and Parseval's theorem
The variance of a single spherical harmonic
We will here demonstrate the relatioship between a function expressed in spherical harmon... | Python Code:
%matplotlib inline
from __future__ import print_function # only necessary if using Python 2.x
import matplotlib.pyplot as plt
import numpy as np
from pyshtools.shclasses import SHCoeffs, SHGrid, SHWindow
lmax = 100
coeffs = SHCoeffs.from_zeros(lmax)
coeffs.set_coeffs(values=[1], ls=[5], ms=[2])
Explanation... |
3,226 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Test application
Autor
Step1: Test data from the application loaded into a simple data container. One row contains the data of a click. If not changed the first file from files is loaded.
|... | Python Code:
files = ['clicks_2020-01-24 09:48:51_touchpad_14"_monitor.csv',
'clicks_2020-01-24 09:44:46_mouse_24"_monitor.csv',
'clicks_2020-01-23 16:00:32_mouse_24"_monitor.csv']
Explanation: Test application
Autor: Nils Verheyen\
Matriculation number: 3043171
Mouse and touchpad input were tested on... |
3,227 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Preparations
Import libraries
Step1: Load data
Step2: Filtering
There are two goals
Step3: Save the hard-earned JDs and skills after all these filters
Step4: Sample job postings
Step5: ... | Python Code:
import my_util as my_util; from my_util import *
Explanation: Preparations
Import libraries:
End of explanation
HOME_DIR = 'd:/larc_projects/job_analytics/'
DATA_DIR = HOME_DIR + 'data/clean/'
# job descriptions (JDs)
init_posts = pd.read_csv(DATA_DIR + 'jd_df.csv')
skill_df = pd.read_csv(DATA_DIR + 'skill... |
3,228 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Feladatok
Minden feladatot külön notebookba oldj meg!
A megoldásnotebook neve tartalmazza a feladat számát!
A megoldasok kerüljenek a MEGOLDASOK mappába!<br> Csak azok a feladatok kerülnek... | Python Code:
a=[12586269025, 20365011074, 32951280099, 53316291173, 86267571272, 139583862445, 225851433717,365435296162, 591286729879,
956722026041, 1548008755920, 2504730781961, 4052739537881, 6557470319842, 10610209857723, 17167680177565, 27777890035288,
44945570212853, 72723460248141, 117669030460994]
b=[832040... |
3,229 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Main Workflow
Step1: Load old colab notebook names
Step2: Parse script names from colab notebooks
Step3: Process the code
Ways to import modules in python
* import foo
* import foo as bar... | Python Code:
from time import time
init = time()
import re
import os
import sys
import json
import yaml
from functools import reduce
from collections import ChainMap
import subprocess
import pandas as pd
from glob import glob
import nbformat
import jax
Explanation: Main Workflow
End of explanation
old_nb_files = glob("... |
3,230 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This notebook contains all of the code from the corresponding post on the One Codex Blog. These snippets are exactly what are in the blog post, and let you perfectly reproduce t... | Python Code:
from onecodex import Api
ocx = Api()
project = ocx.Projects.get("d53ad03b010542e3") # get DIABIMMUNE project by ID
samples = ocx.Samples.where(project=project.id, public=True, limit=50)
samples.metadata[[
"gender",
"host_age",
"geo_loc_name",
"totalige",
"eggs",
"vegetables",
"... |
3,231 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Gaussian processes (GP) are a cornerstone of modern machine learning. They are often used for non-parametric regression and classification, and are extended from the theory behind Gaussian d... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
rng = np.random.RandomState(1999)
n_samples = 1000
X = rng.rand(n_samples)
y = np.sin(20 * X) + .05 * rng.randn(X.shape[0])
X_t = np.linspace(0, 1, 100)
y_t = np.sin(20 * X_t)
plt.scatter(X, y, color='steelblue', label='measured y')
plt.... |
3,232 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualize source leakage among labels using a circular graph
This example computes all-to-all pairwise leakage among 68 regions in
source space based on MNE inverse solutions and a FreeSurfe... | Python Code:
# Authors: Olaf Hauk <olaf.hauk@mrc-cbu.cam.ac.uk>
# Martin Luessi <mluessi@nmr.mgh.harvard.edu>
# Alexandre Gramfort <alexandre.gramfort@inria.fr>
# Nicolas P. Rougier (graph code borrowed from his matplotlib gallery)
#
# License: BSD (3-clause)
import numpy as np
import matplot... |
3,233 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
VIX as a measure of Market Uncertainty
by Brandon Wang (bw1115)
Data Bootcamp Final Project (NYU Stern Spring 2017)
Abstract
The VIX index, calculated and published by the Chicago Board Opti... | Python Code:
# Setup
import sys # system module
import pandas as pd # data package
import matplotlib.pyplot as plt # graphics module
import datetime as dt # date and time module
import seaborn as sns # seaborn graphics module
imp... |
3,234 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Data Science Summer School - Split '17
5. Generating images of digits with Generative Adversarial Networks
Step1: Goals
Step2: What are we going to do with the data?
We have $70000$ images... | Python Code:
%matplotlib inline
%load_ext autoreload
%autoreload 2
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import os, util
Explanation: Data Science Summer School - Split '17
5. Generating images of digits with Generative Adversarial Networks
End of explanation
data_folder = 'data'; d... |
3,235 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
IST256 Lesson 04
Iterations
Zybook Ch 4
P4E Ch5
Links
Participation
Step1: A. 4
B. 5
C. 6
D. 7
Vote Now
Step2: The sequence of code that repeats is known as the Body.
The Boolean express... | Python Code:
i,j,k = 1, 20, 1
while (i<j):
n = k*(j-i)
print(n)
i = i + 1
j = j - 1
k = k * 5
Explanation: IST256 Lesson 04
Iterations
Zybook Ch 4
P4E Ch5
Links
Participation: https://poll.ist256.com
In-Class Questions: Zoom Chat!
Agenda
Exam 1 this week
Go over HW 03
Iterations
Make our code execut... |
3,236 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Hitting and Cold Weather in Baseball
A project by Nathan Ding (njd304@stern.nyu.edu) on the effects of temperature on major league batters
Spring 2016 Semester
Introduction
The Natural Gas L... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
import statsmodels.formula.api as smf
%matplotlib inline
Explanation: Hitting and Cold Weather in Baseball
A project by Nathan Ding (njd304@stern.nyu.edu) on the effects of temperature on major league batters
Spring 2016 Semester
Introduction
The Natural ... |
3,237 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Variational Autoencoders
Introduction
The variational autoencoder (VAE) is arguably the simplest setup that realizes deep probabilistic modeling. Note that we're being careful in our choice ... | Python Code:
import os
import numpy as np
import torch
from pyro.contrib.examples.util import MNIST
import torch.nn as nn
import torchvision.transforms as transforms
import pyro
import pyro.distributions as dist
import pyro.contrib.examples.util # patches torchvision
from pyro.infer import SVI, Trace_ELBO
from pyro.op... |
3,238 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Outline
Glossary
1. Radio Science using Interferometric Arrays
Previous
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
1. Radio Science using Interferometric Arrays
Previous: 1.0 Introduction
Next: 1.2 Electromagnetic radiation and astronomica... |
3,239 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CSE 6040, Fall 2015 [12]
Step1: Exercise. Write a snippet of code to verify that the vertex IDs are dense in some interval $[1, n]$. That is, there is a minimum value of $1$, some maximum v... | Python Code:
import sqlite3 as db
import pandas as pd
def get_table_names (conn):
assert type (conn) == db.Connection # Only works for sqlite3 DBs
query = "SELECT name FROM sqlite_master WHERE type='table'"
return pd.read_sql_query (query, conn)
def print_schemas (conn, table_names=None, limit=0):
asser... |
3,240 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<hr>
Script Development - <code>addPosTags.py</code>
Development notebook for script to add tokens and categories to review data.
<hr>
Setup
Step1: <hr>
Development
Add tri-grams
Step2: Ad... | Python Code:
import pyspark as ps
from sentimentAnalysis import dataProcessing as dp
# create spark session
spark = ps.sql.SparkSession(sc)
# get dataframes
# specify s3 as sourc with s3a://
#df = spark.read.json("s3a://amazon-review-data/user_dedup.json.gz")
#df_meta = spark.read.json("s3a://amazon-review-data/metadat... |
3,241 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 Google LLC.
Licensed under the Apache License, Version 2.0 (the "License");
Step1: Guided ES Demo
This is a fully self-contained notebook that reproduces the toy example in F... | Python Code:
# 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
# distribute... |
3,242 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Notebook-11
Step1: Layout of a Function
As we briefly mentioned in another notebook, any 'word' followed by a set of parenthesis is a function. The 'word' is the function's name, and anythi... | Python Code:
myList = [1,"two", False, 9.99]
len(myList) # A function
print(myList) # A different function!
Explanation: Notebook-11: Introduction to Functions
Lesson Content
Function Anatomy 101
Function definiton & call
Arguments
Return statement
Function calling!
Assign a function to a variable
Function as a paramet... |
3,243 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
This Notebook will help you to identify anomalies in your historical timeseries data (IoT data) in simple steps. Also, derive the threshold value for your historical data. This ... | Python Code:
from pyspark.sql import SQLContext
# adding the PySpark module to SparkContext
sc.addPyFile("https://raw.githubusercontent.com/seahboonsiew/pyspark-csv/master/pyspark_csv.py")
import pyspark_csv as pycsv
# you may need to modify this line if the filename or path is different.
sqlContext = SQLContext(sc)
da... |
3,244 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Convolutional Neural Networks
Step1: Run the next cell to load the "SIGNS" dataset you are going to use.
Step2: As a reminder, the SIGNS dataset is a collection of 6 signs representing num... | Python Code:
import math
import numpy as np
import h5py
import matplotlib.pyplot as plt
import scipy
from PIL import Image
from scipy import ndimage
import tensorflow as tf
from tensorflow.python.framework import ops
from cnn_utils import *
%matplotlib inline
np.random.seed(1)
Explanation: Convolutional Neural Networks... |
3,245 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Network from Nielsen's Chapter 1
http
Step1: Set up Network
Step2: Train Network
Step3: Exercise | Python Code:
import mnist_loader
training_data, validation_data, test_data = mnist_loader.load_data_wrapper()
Explanation: Network from Nielsen's Chapter 1
http://neuralnetworksanddeeplearning.com/chap1.html#implementing_our_network_to_classify_digits
Load MNIST Data
End of explanation
import network
# 784 (28 x 28 pix... |
3,246 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sebastian Raschka, 2016
https
Step1: Bonus Material - Softmax Regression
Softmax Regression (synonyms
Step2: First, we want to encode the class labels into a format that we can more easily... | Python Code:
%load_ext watermark
%watermark -a 'Sebastian Raschka' -u -d -v -p matplotlib,numpy,scipy
# to install watermark just uncomment the following line:
#%install_ext https://raw.githubusercontent.com/rasbt/watermark/master/watermark.py
%matplotlib inline
Explanation: Sebastian Raschka, 2016
https://github.com/r... |
3,247 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src="../Pierian-Data-Logo.PNG">
<br>
<strong><center>Copyright 2019. Created by Jose Marcial Portilla.</center></strong>
Saving and Loading Trained Models
Refer back to this notebook as... | Python Code:
torch.save(model.state_dict(), 'MyModel.pt')
Explanation: <img src="../Pierian-Data-Logo.PNG">
<br>
<strong><center>Copyright 2019. Created by Jose Marcial Portilla.</center></strong>
Saving and Loading Trained Models
Refer back to this notebook as a refresher on saving and loading models.
Saving a trained... |
3,248 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ATTO550, ATT0647N specs
ATTO550
Step1: To obtain the absorption cross-section we need to normalize by the extinctyion coefficient
Step2: Absorption cross-section @ 532 nm | Python Code:
atto550_ext_coeff = 1.2*1e5 # 1 / ( mol cm )
atto647N_ext_coeff = 1.5*1e5 # 1 / ( mol cm )
%matplotlib inline
import matplotlib.pyplot as plt
import pandas as pd
a550 = pd.read_excel('ATTO550.xlsx', 'Tabelle1', index_col=None, na_values=['NA'])
a647N = pd.read_excel('ATTO647N.xlsx', 'Tabelle1', index_co... |
3,249 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Transform EEG data using current source density (CSD)
This script shows an example of how to use CSD
Step1: Load sample subject data
Step2: Plot the raw data and CSD-transformed raw data
S... | Python Code:
# Authors: Alex Rockhill <aprockhill@mailbox.org>
#
# License: BSD (3-clause)
import numpy as np
import matplotlib.pyplot as plt
import mne
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
Explanation: Transform EEG data using current source density (CSD)
This script shows an e... |
3,250 | 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', 'cams', 'sandbox-1', 'aerosol')
Explanation: ES-DOC CMIP6 Model Properties - Aerosol
MIP Era: CMIP6
Institute: CAMS
Source ID: SANDBOX-1
Topic: Aerosol
Sub-Topics: Transport, Emissions... |
3,251 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vectors
A vector is just a point in some finite-dimensional space.
In Python, we can represent a vector as a list of numbers
Step5: Now we will build functions to perform vector arithmetic.... | Python Code:
height_weight_age = [70, # inches
170, # pounds
40] # years
grades = [95, # exam1
80, # exam2
75, # exam3
62] # exam4
Explanation: Vectors
A vector is just a point in some finite-dimensional space.
In Python, we can represent a vecto... |
3,252 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting Started
Magma is a hardware construction language written in Python 3. The central abstraction in Magma is a Circuit, which is analagous to a verilog module. A circuit is a set of fu... | Python Code:
import magma as m
m.set_mantle_target("ice40")
Explanation: Getting Started
Magma is a hardware construction language written in Python 3. The central abstraction in Magma is a Circuit, which is analagous to a verilog module. A circuit is a set of functional units that are wired together.
Magma is designed... |
3,253 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
APS 5 - Questões com auxílio do Pandas
Nome
Step1: Liste as primeiras linhas do DataFrame
Step2: Q1 - Manipulando o DataFrame
Crie uma coluna chamada Hemisfério baseada na Latitude
A regr... | Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import expon
from numpy import arange
import scipy.stats as stats
#Abrir o arquivo
df = pd.read_csv('earthquake.csv')
#listar colunas
print(list(df))
Explanation: APS 5 - Questões com auxílio do Panda... |
3,254 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<span style="color
Step7: Vhanilla RNN class and functions
Step8: Placeholder and initializers
Step9: Models
Step10: Dataset Preparation | Python Code:
import numpy as np
import tensorflow as tf
from sklearn.datasets import load_digits
from sklearn.cross_validation import train_test_split
import pylab as pl
from IPython import display
import sys
%matplotlib inline
Explanation: <span style="color:green"> VANILLA RNN ON 8*8 MNIST DATASET TO PREDICT TEN CLA... |
3,255 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a id='beginning'></a> <!--\label{beginning}-->
* Outline
* Glossary
* 4. The Visibility Space
* Previous
Step1: Import section specific modules
Step2: 4.5.1 UV coverage
Step3: Let's... | 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: <a id='beginning'></a> <!--\label{beginning}-->
* Outline
* Glossary
* 4. The Visibility Space
* Previous: 4.4 The Visibility Function
... |
3,256 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
K Nearest Neighbors Classifiers
So far we've covered learning via probability (naive Bayes) and learning via errors (regression). Here we'll cover learning via similarity. This means we look... | Python Code:
music = pd.DataFrame()
# Some data to play with.
music['duration'] = [184, 134, 243, 186, 122, 197, 294, 382, 102, 264,
205, 110, 307, 110, 397, 153, 190, 192, 210, 403,
164, 198, 204, 253, 234, 190, 182, 401, 376, 102]
music['loudness'] = [18, 34, 43, 36, 22, 9, ... |
3,257 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework #4
These problem sets focus on list comprehensions, string operations and regular expressions.
Problem set #1
Step1: In the following cell, complete the code with an expression tha... | Python Code:
numbers_str = '496,258,332,550,506,699,7,985,171,581,436,804,736,528,65,855,68,279,721,120'
Explanation: Homework #4
These problem sets focus on list comprehensions, string operations and regular expressions.
Problem set #1: List slices and list comprehensions
Let's start with some data. The following cell... |
3,258 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocnbgchem
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', 'mri', 'sandbox-1', 'ocnbgchem')
Explanation: ES-DOC CMIP6 Model Properties - Ocnbgchem
MIP Era: CMIP6
Institute: MRI
Source ID: SANDBOX-1
Topic: Ocnbgchem
Sub-Topics: Tracers.
Proper... |
3,259 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Python Jupyter
Welcome to Jupyter, through this interface I will be showing you the following
Step1: Cleaning Up The Full Text
In order for better results from our analysis ... | Python Code:
import json
import requests
apiResponse = requests.get('https://oc-index.library.ubc.ca/collections/bcbooks/items/1.0059569').json()
item = apiResponse['data']
fullText = item['FullText'][0]['value']
print(fullText)
Explanation: Introduction to Python Jupyter
Welcome to Jupyter, through this interface I wi... |
3,260 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: TV Script Generation
In this project, you'll generate your own Simpsons TV scripts using RNNs. You'll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Ne... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
Explanation: TV Script Generation
In this project, you'll generate your own Simpsons TV script... |
3,261 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting Started
This is an Notebook containing the examples from the Getting Started section in the documentation. Refer to the documentation for very verbose description of this code.
Optim... | Python Code:
# import the classes we need
from SafeRLBench.envs import LinearCar
from SafeRLBench.policy import LinearPolicy
from SafeRLBench.algo import PolicyGradient
# get an instance of `LinearCar` with the default arguments.
linear_car = LinearCar()
# we need a policy which maps R^2 to R
policy = LinearPolicy(2, 1... |
3,262 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Basics
Thunder provides data structures, read/write patterns, and simple processing of spatial and temporal data. All operations in Thunder are designed to scale to very large data sets thro... | Python Code:
import thunder as td
series = td.series.fromexample('fish')
Explanation: Basics
Thunder provides data structures, read/write patterns, and simple processing of spatial and temporal data. All operations in Thunder are designed to scale to very large data sets through the distributed comptuing engine Spark, ... |
3,263 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Running pyqz I
A) Installing and importing pyqz
Installing pyqz is best done via pip. You should then be able to import the package and check its version from within any Python shell
Step1: ... | Python Code:
%matplotlib inline
import pyqz
import numpy as np
Explanation: Running pyqz I
A) Installing and importing pyqz
Installing pyqz is best done via pip. You should then be able to import the package and check its version from within any Python shell:
End of explanation
import pyqz.pyqz_plots as pyqzp
Explanati... |
3,264 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Adding new passbands to PHOEBE
In this tutorial we will show you how to add your own passband to PHOEBE. Adding a custom passband involves
Step1: If you plan on computing model atmosphere i... | Python Code:
#!pip install -I "phoebe>=2.4,<2.5"
Explanation: Adding new passbands to PHOEBE
In this tutorial we will show you how to add your own passband to PHOEBE. Adding a custom passband involves:
downloading and setting up model atmosphere tables;
providing a passband transmission function;
defining and registeri... |
3,265 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center">Logistic Regression in TensorFlow</h1>
In this notebook, we illustrate the basics of Logistic Regression using TensorFlow, on the <a href="https
Step1: Feature Informatio... | Python Code:
import numpy as np
import pandas as pd
%pylab inline
pylab.style.use('ggplot')
url = 'https://archive.ics.uci.edu/ml/machine-learning-databases/pima-indians-diabetes/pima-indians-diabetes.data'
pima_df = pd.read_csv(url, header=None)
Explanation: <h1 align="center">Logistic Regression in TensorFlow</h1>
In... |
3,266 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
20. 자연어처리
1) 워드 클라우드
단어의 크기를 단어의 빈도 수에 비례하도록 하여 단어를 아름답게 배치
Step2: 아주 멋있어 보이기는 하지만, 딱히 어떤 정보를 제공하지는 않는다.
단어가 구인 광고에 등장하는 빈도를 가로축,
단어가 이력서에 등장하는 빈도를 세로축
Step3: 2) n-gram 모델
Step4: bigram
... | Python Code:
import math, random, re
from collections import defaultdict, Counter
from bs4 import BeautifulSoup
import requests
import matplotlib.pyplot as plt
#데이터 과학 관련 키워드목록, 빈도 0~100
data = [ ("big data", 100, 15), ("Hadoop", 95, 25), ("Python", 75, 50),
("R", 50, 40), ("machine learning", 80, 20), ("stati... |
3,267 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Examples of split
A split agent has a single input stream and two or more output streams.
Step1: split_element
<b>split_element(func, in_stream, out_streams)</b>
<br>
<br>
where
<ol>
<l... | Python Code:
import os
import sys
sys.path.append("../")
from IoTPy.core.stream import Stream, run
from IoTPy.agent_types.split import split_element, split_list, split_window
from IoTPy.agent_types.split import unzip, separate, timed_unzip
from IoTPy.agent_types.basics import split_e, fsplit_2e
from IoTPy.helper_functi... |
3,268 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Interpolation Exercise 1
Step1: 2D trajectory interpolation
The file trajectory.npz contains 3 Numpy arrays that describe a 2d trajectory of a particle as a function of time
Step2: Use the... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import seaborn as sns
import numpy as np
from scipy.interpolate import interp1d
Explanation: Interpolation Exercise 1
End of explanation
dictionary = np.load('trajectory.npz')
y = dictionary.items()[0][1]
t = dictionary.items()[1][1]
x = dictionary.items()... |
3,269 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<p style="text-align
Step2: 1. Implementar o algoritmo K-means
Nesta etapa você irá implementar as funções que compõe o algoritmo do KMeans uma a uma. É importante entender e ler a document... | Python Code:
# import libraries
# linear algebra
import numpy as np
# data processing
import pandas as pd
# data visualization
from matplotlib import pyplot as plt
# load the data with pandas
dataset = pd.read_csv('dataset.csv', header=None)
dataset = np.array(dataset)
plt.scatter(dataset[:,0], dataset[:,1], s=10)
p... |
3,270 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Split matrix randomly into train, valid and test sets
Step1: Select random batch
This can be used for mini-batch training.
Step2: Using sklearn
Scikit-learn has a train_test_split function... | Python Code:
import numpy as np
# matrix dimensions
N = 100
M = 20
# train-valid-test ratio, let's use 80-10-10
train_ratio = 0.8
valid_ratio = 0.1
test_ratio = 1.0 - train_ratio - valid_ratio # this is never used
# array indices
train_split = int(train_ratio * N)
valid_split = int(valid_ratio * N)
# create a random m... |
3,271 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
用不到 50 行代码训练 GAN（基于 PyTorch
本文作者为前谷歌高级工程师、AI 初创公司 Wavefront 创始人兼 CTO Dev Nag，介绍了他是如何用不到五十行代码，在 PyTorch 平台上完成对 GAN 的训练。
什么是 GAN？
在进入技术层面之前，为照顾新入门的开发者，先来介绍下什么是 GAN。
2014 年，Ian Goodfellow 和他在蒙特... | Python Code:
# Generative Adversarial Networks (GAN) example in PyTorch.
# See related blog post at https://medium.com/@devnag/generative-adversarial-networks-gans-in-50-lines-of-code-pytorch-e81b79659e3f#.sch4xgsa9
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim... |
3,272 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Object Model
bqplot is based on Grammar of Graphics paradigm. The Object Model in bqplot gives the user the full flexibility to build custom plots. This means the API is verbose but fully cu... | Python Code:
from bqplot import (
LinearScale,
Axis,
Figure,
OrdinalScale,
LinearScale,
Bars,
Lines,
Scatter,
)
# first, let's create two vectors x and y to plot using a Lines mark
import numpy as np
x = np.linspace(-10, 10, 100)
y = np.sin(x)
# 1. Create the scales
xs = LinearScale()
ys... |
3,273 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TensorFlow Tutorial #12
Adversarial Noise for MNIST
by Magnus Erik Hvass Pedersen
/ GitHub / Videos on YouTube
Introduction
The previous Tutorial #11 showed how to find so-called adversarial... | Python Code:
from IPython.display import Image
Image('images/12_adversarial_noise_flowchart.png')
Explanation: TensorFlow Tutorial #12
Adversarial Noise for MNIST
by Magnus Erik Hvass Pedersen
/ GitHub / Videos on YouTube
Introduction
The previous Tutorial #11 showed how to find so-called adversarial examples for a sta... |
3,274 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent neural network that performs sentiment analysis. Using an RNN rather than a feedfoward network is more accurate ... | Python Code:
import numpy as np
import tensorflow as tf
with open('../sentiment-network/reviews.txt', 'r') as f:
reviews = f.read()
with open('../sentiment-network/labels.txt', 'r') as f:
labels = f.read()
reviews[:2000]
Explanation: Sentiment Analysis with an RNN
In this notebook, you'll implement a recurrent ... |
3,275 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2021 The TF-Agents Authors.
Step1: Actor-Learner API를 사용한 SAC minitaur
<table class="tfo-notebook-buttons" align="left">
<td> <a target="_blank" href="https
Step2: 설정
먼저 필요... | 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... |
3,276 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Here we will test parameter recovery and model comparison for Rescorla-Wagner (RW), Hierarchical Gaussian Filters (HGF), and Switching Gaussian Filters (SGF) models of the social influence t... | Python Code:
import numpy as np
from scipy import io
import matplotlib.pyplot as plt
import seaborn as sns
import pandas as pd
sns.set(style = 'white', color_codes = True)
%matplotlib inline
import sys
import os
import os
cwd = os.getcwd()
sys.path.append(cwd[:-len('befit/examples/social_influence')])
Explanation: Here... |
3,277 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Differentially Private Histograms
Plotting the distribution of ages in Adult
Step1: We first read in the list of ages in the Adult UCI dataset (the first column).
Step2: Using Numpy's nati... | Python Code:
import numpy as np
from diffprivlib import tools as dp
import matplotlib.pyplot as plt
Explanation: Differentially Private Histograms
Plotting the distribution of ages in Adult
End of explanation
ages_adult = np.loadtxt("https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data",
... |
3,278 | 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', 'nerc', 'ukesm1-0-ll', 'land')
Explanation: ES-DOC CMIP6 Model Properties - Land
MIP Era: CMIP6
Institute: NERC
Source ID: UKESM1-0-LL
Topic: Land
Sub-Topics: Soil, Snow, Vegetation, E... |
3,279 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fluxing with PYPIT [v2]
Step1: For the standard User (Running the script)
Generate the sensitivity function from an extracted standard star
Here is an example fluxing file (see the fluxing ... | Python Code:
%matplotlib inline
# import
from importlib import reload
import os
from matplotlib import pyplot as plt
import glob
import numpy as np
from astropy.table import Table
from pypeit import fluxspec
from pypeit.spectrographs.util import load_spectrograph
Explanation: Fluxing with PYPIT [v2]
End of explanation
... |
3,280 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
My sample df has four columns with NaN values. The goal is to concatenate all the kewwords rows from end to front while excluding the NaN values. | Problem:
import pandas as pd
import numpy as np
df = pd.DataFrame({'users': ['Hu Tao', 'Zhongli', 'Xingqiu'],
'keywords_0': ["a", np.nan, "c"],
'keywords_1': ["d", "e", np.nan],
'keywords_2': [np.nan, np.nan, "b"],
'keywords_3': ["f", np.nan, "... |
3,281 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
License
Copyright 2017 J. Patrick Hall, jphall@gwu.edu
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "... | Python Code:
# imports
import h2o
import operator
import numpy as np
import pandas as pd
from h2o.estimators.glm import H2OGeneralizedLinearEstimator
from h2o.estimators.gbm import H2OGradientBoostingEstimator
# start h2o
h2o.init()
h2o.remove_all()
Explanation: License
Copyright 2017 J. Patrick Hall, jphall@gwu.edu
P... |
3,282 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Intro to Neural Networks
Handwritten Digits Recognization
<img src = './img/neuralnetwork/neuron2.png' width = 700 align = 'left'>
<img src = './img/neuralnetwork/synapse.jpg' width = 150 al... | Python Code:
1*0.25 + 0.5*(-1.5)
Explanation: Intro to Neural Networks
Handwritten Digits Recognization
<img src = './img/neuralnetwork/neuron2.png' width = 700 align = 'left'>
<img src = './img/neuralnetwork/synapse.jpg' width = 150 align = 'right'>
The Neuron: A Biological Information Processor
dentrites - the rece... |
3,283 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Twitter API rate limits
Step1: Calculating remaining time (in mins) before api limits reset
I find it helpful to check how many more minutes I have to wait before trying again
Step2: Key f... | Python Code:
### checking rate limit - friends list
limit = api.rate_limit_status()
limit['resources']['friends']['/friends/list']['remaining']
limit['resources']['friends']['/friends/list']
Explanation: Twitter API rate limits
End of explanation
import datetime as dt
given_date =dt.datetime.fromtimestamp(
int(... |
3,284 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Advanced
Step1: As always, let's do imports and initialize a logger and a new Bundle. See Building a System for more details.
Step2: And we'll attach some dummy datasets. See Datasets fo... | Python Code:
!pip install -I "phoebe>=2.2,<2.3"
Explanation: Advanced: Alternate Backends
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 update to the latest release).
End of explanation
import ph... |
3,285 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
Without getting too detailed Lab is about a simple technique for either increasing or decreasing the playing time of a sound array, without altering the sound's pitch. Increasin... | Python Code:
Image('images/PyAudio_RT_flow@300dpi.png',width='80%')
pah.available_devices()
Explanation: Introduction
Without getting too detailed Lab is about a simple technique for either increasing or decreasing the playing time of a sound array, without altering the sound's pitch. Increasing the rate refers to decr... |
3,286 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step1: We define the model, adapted from the Keras CIFAR-10 example
Step2: We train the model us... | Python Code:
import tensorflow as tf
# Check that GPU is available: cf. https://colab.research.google.com/notebooks/gpu.ipynb
assert(tf.test.gpu_device_name())
tf.keras.backend.clear_session()
tf.config.optimizer.set_jit(False) # Start with XLA disabled.
def load_data():
(x_train, y_train), (x_test, y_test) = tf.kera... |
3,287 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: TV Script Generation
In this project, you'll generate your own Simpsons TV scripts using RNNs. You'll be using part of the Simpsons dataset of scripts from 27 seasons. The Neural Ne... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL
import helper
data_dir = './data/simpsons/moes_tavern_lines.txt'
text = helper.load_data(data_dir)
# Ignore notice, since we don't use it for analysing the data
text = text[81:]
Explanation: TV Script Generation
In this project, you'll generate your own Simpsons TV script... |
3,288 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Protein binding & undfolding – a four-state model
In this notebook we will look into a the kinetics of a model system describing competing protein folding, aggregation and ligand binding. Us... | Python Code:
import logging; logger = logging.getLogger('matplotlib'); logger.setLevel(logging.INFO) # or notebook filled with logging
from collections import OrderedDict, defaultdict
import math
import re
import time
from IPython.display import Image, Latex, display
import matplotlib.pyplot as plt
import sympy
from p... |
3,289 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: Model Averaging
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Build Model
Step3: Prepare... | 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... |
3,290 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Creating a custom prediction routine with scikit-learn
<table align="left">
<td>
<a href="https
Step1: Authenticate your GCP account
If you are using AI Platform Notebooks, your envir... | Python Code:
PROJECT_ID = "<your-project-id>" #@param {type:"string"}
! gcloud config set project $PROJECT_ID
Explanation: Creating a custom prediction routine with scikit-learn
<table align="left">
<td>
<a href="https://cloud.google.com/ml-engine/docs/scikit/custom-prediction-routine-scikit-learn">
<img sr... |
3,291 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1> Getting started with TensorFlow </h1>
In this notebook, you play around with the TensorFlow Python API.
Step1: <h2> Adding two tensors </h2>
First, let's try doing this using numpy, th... | Python Code:
import tensorflow as tf
import numpy as np
print(tf.__version__)
Explanation: <h1> Getting started with TensorFlow </h1>
In this notebook, you play around with the TensorFlow Python API.
End of explanation
a = np.array([5, 3, 8])
b = np.array([3, -1, 2])
c = np.add(a, b)
print(c)
Explanation: <h2> Adding t... |
3,292 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Matplotlib Exercise 2
Imports
Step1: Exoplanet properties
Over the past few decades, astronomers have discovered thousands of extrasolar planets. The following paper describes the propertie... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import math
Explanation: Matplotlib Exercise 2
Imports
End of explanation
!head -n 30 open_exoplanet_catalogue.txt
Explanation: Exoplanet properties
Over the past few decades, astronomers have discovered thousands of extrasolar planets. ... |
3,293 | Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
I have a dataframe with one of its column having a list at each index. I want to concatenate these lists into one string like '1,2,3,4,5'. I am using | Problem:
import pandas as pd
df = pd.DataFrame(dict(col1=[[1, 2, 3]] * 2))
def g(df):
L = df.col1.sum()
L = map(lambda x:str(x), L)
return ','.join(L)
result = g(df.copy()) |
3,294 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Latitude-dependent grey radiation
Here is a quick example of using the climlab.GreyRadiationModel with a latitude dimension and seasonally varying insolation.
Step1: Testing out multi-dimen... | Python Code:
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
import climlab
from climlab import constants as const
model = climlab.GreyRadiationModel(name='Grey Radiation', num_lev=30, num_lat=90)
print(model)
model.to_xarray()
insolation = climlab.radiation.DailyInsolation(domains=model.Ts.domain... |
3,295 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Classification - MNIST dataset
Exploring the popular MNIST dataset.
Tensorflow provides a function to ingest the data.
Step1: A little exploration
Step2: Lets look at a random image and i... | Python Code:
# Necessary imports
import time
from IPython import display
import numpy as np
from matplotlib.pyplot import imshow
from PIL import Image, ImageOps
import tensorflow as tf
%matplotlib inline
from tensorflow.examples.tutorials.mnist import input_data
# Read the mnist dataset
mnist = input_data.read_data_set... |
3,296 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of the code, but left the implementat... | Python Code:
%matplotlib inline
%config InlineBackend.figure_format = 'retina'
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
Explanation: Your first neural network
In this project, you'll build your first neural network and use it to predict daily bike rental ridership. We've provided some of t... |
3,297 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This notebook was created by Sergey Tomin for Workshop
Step1: Tutorials
Preliminaries
Step2: <a id="tutorial1"></a>
Tutorial N1. Double Bend Achromat.
We designed a simple lattice to demon... | Python Code:
from IPython.display import Image
#Image(filename='gui_example.png')
Explanation: This notebook was created by Sergey Tomin for Workshop: Designing future X-ray FELs. Source and license info is on GitHub. August 2016.
An Introduction to Ocelot
Ocelot is a multiphysics simulation toolkit designed for studyi... |
3,298 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
2016 NHL Hockey Data Set - Sasha Kandrach
Step1: Here's all of our data
Step2: Here are each of the columns in the data set
Step3: Let's count how many players are from each country
Step4... | Python Code:
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
df= pd.read_excel("NHL 2014-15.xls")
!pip install xlrd
df.columns.value_counts()
Explanation: 2016 NHL Hockey Data Set - Sasha Kandrach
End of explanation
df.head()
Explanation: Here's all of our data:
End of explanation
df.columns
Ex... |
3,299 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
En este documento se describen los pasos llevados a cabo para estandarizar los datos disponibles desde la encuesta intercensal y utilizarlos para la construcción de parámetros. Las limpieza ... | Python Code:
# Librerias utilizadas
import pandas as pd
import sys
import urllib
import os
import numpy as np
# Configuracion del sistema
print('Python {} on {}'.format(sys.version, sys.platform))
print('Pandas version: {}'.format(pd.__version__))
import platform; print('Running on {} {}'.format(platform.system(), plat... |
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