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2,200 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Supervised Learning
Step1: One approach to building a predictive model is to subdivide the variable space into regions, by sequentially subdividing each variable. For example, if we split l... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
sns.set()
from sklearn.datasets import load_diabetes
# Predictors: "age" "sex" "bmi" "map" "tc" "ldl" "hdl" "tch" "ltg" "glu"
diabetes = load_diabetes()
y = diabetes['target']
bmi, ltg = diabete... |
2,201 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to Bayesian Optimization with GPyOpt
Written by Javier Gonzalez, Amazon Research Cambridge
Last updated Monday, 22 May 2017.
====================================================... | Python Code:
%pylab inline
import GPy
import GPyOpt
from numpy.random import seed
import matplotlib
Explanation: Introduction to Bayesian Optimization with GPyOpt
Written by Javier Gonzalez, Amazon Research Cambridge
Last updated Monday, 22 May 2017.
===================================================================... |
2,202 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analysis of Monte Carlo simulations of mutation accumulation in stem cells
This Notebook lives at Github.
Many adult tissues renew themselves continually via a pool of cells called stem cel... | Python Code:
from IPython.display import Image
Image(filename="trajectories.png", width=350, height=350)
Explanation: Analysis of Monte Carlo simulations of mutation accumulation in stem cells
This Notebook lives at Github.
Many adult tissues renew themselves continually via a pool of cells called stem cells. Stem cel... |
2,203 | Given the following text description, write Python code to implement the functionality described.
Description:
Length of longest common prefix possible by rearranging strings in a given array
Python3 program to implement the above approach ; Function to get the length of the longest common prefix by rearranging the str... | Python Code:
import sys
def longComPre(arr , N ) :
freq =[[ 0 for i in range(256 ) ] for i in range(N ) ]
for i in range(N ) :
M = len(arr[i ] )
for j in range(M ) :
freq[i ][ord(arr[i ][j ] ) ] += 1
maxLen = 0
for j in range(256 ) :
minRowVal = sys . maxsize
for i in range(N ) :
minRowVa... |
2,204 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<font color='blue'>Data Science Academy - Python Fundamentos - Capítulo 8</font>
Download
Step1: NumPy
Para importar numpy, utilize
Step2: Criando Arrays
Step3: Funções NumPy
Step4: Cria... | Python Code:
# Versão da Linguagem Python
from platform import python_version
print('Versão da Linguagem Python Usada Neste Jupyter Notebook:', python_version())
Explanation: <font color='blue'>Data Science Academy - Python Fundamentos - Capítulo 8</font>
Download: http://github.com/dsacademybr
End of explanation
# Imp... |
2,205 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Symbol Tutorial
Besides the tensor computation interface NDArray, another main object in MXNet is the Symbol provided by mxnet.symbol, or mxnet.sym for short. A symbol represents a multi-out... | Python Code:
import mxnet as mx
a = mx.sym.Variable('a')
b = mx.sym.Variable('b')
c = a + b
(a, b, c)
Explanation: Symbol Tutorial
Besides the tensor computation interface NDArray, another main object in MXNet is the Symbol provided by mxnet.symbol, or mxnet.sym for short. A symbol represents a multi-output symbolic ex... |
2,206 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create Data Processing Functions
Step2: Create Data Pipeline
Step3: Send First Two Pieces Of Raw Data Through Pipeline
Step4: Send All Raw Data Through Pipeline | Python Code:
raw_data = [1,2,3,4,5,6,7,8,9,10]
Explanation: Title: Streaming Data Pipeline
Slug: streaming_data_pipeline
Summary: Streaming Data Pipeline Using Python.
Date: 2017-02-02 12:00
Category: Python
Tags: Basics
Authors: Chris Albon
Create Some Raw Data
End of explanation
# Define a generator that yields inp... |
2,207 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Homework 3 Problem 5
Step1: Part 5.a.
Here we load the large mandrill image and display it.
Step2: Part 5.b.
Here we load the small mandrill image and display it.
Step3: Now apply the K-M... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
import kmeans
KCENTROIDS = 16
MAX_ITERS = 200
EPSILON = 1e-7
Explanation: Homework 3 Problem 5
End of explanation
Ilarge = plt.imread('mandrill-large.tiff')
Ilarge = np.uint8(np.round(Ilarge))
plt.imshow(Ilarge)
plt.show()
Explanation: Part 5.a.
Here we lo... |
2,208 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Alcune applicazioni delle matrici
Subito dopo aver introdotto le matrici e viste le operazioni fondamentali di somma, prodotto e determinante una domanda sorge spontanea. A cosa servono? In ... | Python Code:
import sys; sys.path.append('pyggb')
%reload_ext geogebra_magic
%ggb --width 800 --height 400 --showToolBar 0 --showResetIcon 1 trasformazioni.ggb
Explanation: Alcune applicazioni delle matrici
Subito dopo aver introdotto le matrici e viste le operazioni fondamentali di somma, prodotto e determinante una d... |
2,209 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fine-tuning a CNN with MXNet
Step1: Dowload pre-trained model from the model zoo (Resnet-152)
We then download a pretrained 152-layer ResNet model and load into memory.
Note
Step3: Fine tu... | Python Code:
# Data Iterators for cats vs dogs dataset
import mxnet as mx
def get_iterators(batch_size, data_shape=(3, 224, 224)):
train = mx.io.ImageRecordIter(
path_imgrec = './cats_dogs_train.rec',
data_name = 'data',
label_name = 'softmax_label',
batch... |
2,210 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multi-Dimension Visualization
Step1: Scatter Matrix
The scatter matrix allows users to identify correlations between pairs of dimensions in a matrix form.
Step2: Histograms
Once you want i... | Python Code:
%matplotlib inline
import os
import pandas as pd
import seaborn as sns
import matplotlib as mpl
import matplotlib.pyplot as plt
# Setup context and style
sns.set_context('talk')
sns.set_style('whitegrid')
IRIS = os.path.join("..", "data", "iris.csv")
data = pd.read_csv(IRIS)
Explanation: Multi-Dimension... |
2,211 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Ausgeführtes Beispiel für den Buchberger-Algorithmus
Step1: Zuerst wird ein Polynomring geschaffen. QQ ist $\mathbb Q$. Alternative Termordnungen sind grlex und grevlex.
Step2: Es gibt a... | Python Code:
from sympy import *
init_printing()
Explanation: Ausgeführtes Beispiel für den Buchberger-Algorithmus
End of explanation
P, erzeuger = xring('x,y', QQ, lex)
x, y = erzeuger
def S_poly(p, q):
kgv = p.leading_monom().lcm(q.leading_monom())
t1 = kgv / p.leading_term() * p
t2 = kgv / q.leading_term... |
2,212 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Experiments for extracting images of Boyd's Bird Journal into computer readable form
(See image below)
The journals are PDFs containing a series of scanned images of observations of birds. T... | Python Code:
%load_ext watermark
%watermark -a 'Raphael LaFrance' -i -u -v -r -g -p numpy,matplotlib,skimage
Explanation: Experiments for extracting images of Boyd's Bird Journal into computer readable form
(See image below)
The journals are PDFs containing a series of scanned images of observations of birds. The obser... |
2,213 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Demo 2 - Remote parallel computation [distributed]
Demo for site visit | Brendan Smithyman | April 8, 2015
Choice of IPython / jupyter cluster profile
Step1: Importing libraries
numpy is th... | Python Code:
# profile = 'phobos' # remote workstation
# profile = 'pantheon' # remote cluster
profile = 'mpi' # local machine
Explanation: Demo 2 - Remote parallel computation [distributed]
Demo for site visit | Brendan Smithyman | April 8, 2015
Choice of IPython / jupyter cluster profile
End of explanation
import n... |
2,214 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
In this notebook an estimator for the Volume will be trained. No hyperparameters will be searched for, and the ones from the 'Close' values estimator will be used instead.
Step1: Let's gene... | Python Code:
# Basic imports
import os
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import scipy.optimize as spo
import sys
from time import time
from sklearn.metrics import r2_score, median_absolute_error
%matplotlib inline
%pylab inline
pylab.rcParams['figure.figsize'] ... |
2,215 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Take a look at a typical review. This one is labeled "negative"
Step2: Check for missing values
Step3: 35 records show NaN (this stands for "not a number" and is equi... | Python Code:
import numpy as np
import pandas as pd
df = pd.read_csv('../TextFiles/moviereviews.tsv', sep='\t')
df.head()
len(df)
Explanation: <a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>
Text Classification Project
Now we're at the point where we should be able to:
* Read in a colle... |
2,216 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
简单线图
先设置ipython notebook 作图环境
Step1: 对于所有Matplotlib图，我们首先创建一个图形和一个轴。以最简单的形式，可以如下创建图形和轴：
Step2: 在Matplotlib中，图形（类plt.Figure的一个实例）可以被认为是一个包含所有代表轴，图形，文本和标签的对象的容器。轴（类plt.Axes的实例）就是我们在上面看到的：一个带... | Python Code:
%matplotlib inline
import matplotlib.pyplot as plt
#使用seaborn-whitegrid风格
plt.style.use('seaborn-whitegrid')
import numpy as np
Explanation: 简单线图
先设置ipython notebook 作图环境
End of explanation
fig = plt.figure()
ax = plt.axes()
Explanation: 对于所有Matplotlib图，我们首先创建一个图形和一个轴。以最简单的形式，可以如下创建图形和轴：
End of explanation... |
2,217 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Electric Machinery Fundamentals 5th edition
Chapter 2 (Code examples)
Example 2-5
Calculate and plot the voltage regulation of a transformer as a function of load for power factors of 0.8 l... | Python Code:
%pylab notebook
Explanation: Electric Machinery Fundamentals 5th edition
Chapter 2 (Code examples)
Example 2-5
Calculate and plot the voltage regulation of a transformer as a function of load for power factors of 0.8 lagging, 1.0, and 0.8 leading.
Import the PyLab namespace (provides set of useful command... |
2,218 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
T-shirt inspiration
❝first solve the problem then write the code❞
Step1: Introduction
This Jupyter notebook is a place to keep my thoughts organized on how to best present Fort Lauderdale P... | Python Code:
from IPython.display import IFrame
IFrame(
'https://www.sunfrog.com/Geek-Tech/First-solve-the-problem-Then-write-the-code.html',
width=800,
height=350,
)
Explanation: T-shirt inspiration
❝first solve the problem then write the code❞
End of explanation
from IPython.display import IFrame
IFrame... |
2,219 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ApJdataFrames 001
Step1: We're skipping Table 1 because it is an observing log.
Table 2- Members of IC348
Since this table is formatted in the CDS format, it is easiest to take advantage of... | Python Code:
%pylab inline
import seaborn as sns
sns.set_context("notebook", font_scale=1.5)
import warnings
warnings.filterwarnings("ignore")
Explanation: ApJdataFrames 001: Luhman2003
Title: A Census of the Young Cluster IC 348
Authors: Luhman K.L., Stauffer J.R., Muench A.A., Rieke G.H., Lada E.A., Bouvier J., Lada ... |
2,220 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Title
Step1: Create an example dataframe
Step2: List Comprehensions
As a loop
Step3: As list comprehension | Python Code:
# Import modules
import pandas as pd
# Set ipython's max row display
pd.set_option('display.max_row', 1000)
# Set iPython's max column width to 50
pd.set_option('display.max_columns', 50)
Explanation: Title: Using List Comprehensions With Pandas
Slug: pandas_list_comprehension
Summary: Using List Comprehen... |
2,221 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align="center"> Introdução ao Processamento de Linguagem Natural (PLN) Usando Python </h1>
<h3 align="center"> Professor Fernando Vieira da Silva MSc.</h3>
<h2> Técnicas para Pré-Process... | Python Code:
import nltk
nltk.download("gutenberg")
Explanation: <h1 align="center"> Introdução ao Processamento de Linguagem Natural (PLN) Usando Python </h1>
<h3 align="center"> Professor Fernando Vieira da Silva MSc.</h3>
<h2> Técnicas para Pré-Processamento </h2>
<p>Vamos avaliar as técnicas mais comuns para prepar... |
2,222 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Idomatic Pandas
Q
Step1: Reshaping DataFrame objects
In the context of a single DataFrame, we are often interested in re-arranging the layout of our data.
This dataset in from Table 6.9 of... | Python Code:
%matplotlib inline
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
Explanation: Idomatic Pandas
Q: How do I make my pandas code faster with parallelism?
A: You don’t need parallelism, you can use Pandas better.
-- Matthew Rocklin
Now that we have been exposed to the basic functionali... |
2,223 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression Models
By Saurabh Mahindre - <a href="https
Step1: Training and generating weights
LeastSquaresRegression has to be initialised with the training features and training labels. On... | Python Code:
%pylab inline
%matplotlib inline
import os
SHOGUN_DATA_DIR=os.getenv('SHOGUN_DATA_DIR', '../../../data')
from cycler import cycler
# import all shogun classes
from shogun import *
slope = 3
X_train = rand(30)*10
y_train = slope*(X_train)+random.randn(30)*2+2
y_true = slope*(X_train)+2
X_test = concatenate(... |
2,224 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: トレーニング後の float16 量子化
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: モデルをトレーニングしてエクスポートする
Step3:... | 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... |
2,225 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Random Numbers in NumPy
Step1: The numpy.random module adds to the standard built-in Python random functions for generating efficiently whole arrays of sample values with many kinds of prob... | Python Code:
import numpy as np
Explanation: Random Numbers in NumPy
End of explanation
samples = np.random.normal(size=(4,4))
samples
Explanation: The numpy.random module adds to the standard built-in Python random functions for generating efficiently whole arrays of sample values with many kinds of probability distri... |
2,226 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
函数调用的参数规则与解包
Python 的函数在声明参数时大概有下面 4 种形式：
不带默认值的：def func(a)
Step1: 另外一条规则是：位置参数优先权：
Step2: 最保险的方法就是全部采用关键词参数。
任意参数
任意参数可以接受任意数量的参数，其中*a的形式代表任意数量的位置参数，**d代表任意数量的关键词参数：
Step3: 上面的这个def con... | Python Code:
def func(a, b = 1):
pass
func(a = "G", 20) # SyntaxError 语法错误
Explanation: 函数调用的参数规则与解包
Python 的函数在声明参数时大概有下面 4 种形式：
不带默认值的：def func(a): pass
带有默认值的：def func(a, b = 1): pass
任意位置参数：def func(a, b = 1, *c): pass
任意键值参数：def func(a, b = 1, *c, **d): pass
在调用函数时，有两种情况：
没有关键词的参数：func("G", 20)
带有关键词的参数：func(a... |
2,227 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Common Cross Validation Test Code
We used the same cross validation test procedure for the three applications described in the paper. This document provides explanations for the code in anal... | Python Code:
# The 'combined' list has all the 22 metrics
feature_names_combined = (
'entities', 'agents', 'activities', # PROV types (for nodes)
'nodes', 'edges', 'diameter', 'assortativity', # standard metrics
'acc', 'acc_e', 'acc_a', 'acc_ag', # average clustering coefficients
'mfd_e_e', 'mfd_e_a'... |
2,228 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Twitter Sentiment Analysis
Businesses and organizations around the world know that the first requirement for success is a happy customer base. For the purpose of identifying customer sentime... | Python Code:
import swat
from IPython.display import display
swat.options.cas.exception_on_severity = 2
s = swat.CAS('rdcgrd075.unx.sas.com', 3217,authinfo=r'/u/saleem/.authinfo')
s.loadactionset('deeplearn')
Explanation: Twitter Sentiment Analysis
Businesses and organizations around the world know that the first requi... |
2,229 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
NumPy Basics
Numerical Python, or "NumPy" for short, is a foundational package on which many of the most common data science packages are built. Numpy provides us with high performance mult... | Python Code:
import numpy as np
from __future__ import print_function
Explanation: NumPy Basics
Numerical Python, or "NumPy" for short, is a foundational package on which many of the most common data science packages are built. Numpy provides us with high performance multi-dimensional arrays which we can use as vector... |
2,230 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 style="text-align
Step1: Next-word prediction task
Part 1
Step2: 1.2.Symbols encoding
The LSTM input's can only be numbers. A way to convert words (symbols or any items) to numbers is ... | Python Code:
import numpy as np
import collections # used to build the dictionary
import random
import time
from time import time
import pickle # may be used to save your model
import matplotlib.pyplot as plt
#Import Tensorflow and rnn
import tensorflow as tf
from tensorflow.contrib import rnn
# Target log path
logs... |
2,231 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
tidy-harness
A tidy pandas.DataFrame with scikit-learn models, interactive bokeh visualizations, and jinja2 templates.
Usage
Example
Step1: More Examples
More examples can be found in the t... | Python Code:
import harness
from harness import Harness
from pandas import Categorical
from sklearn import datasets, discriminant_analysis
iris = datasets.load_iris()
# Harness is just a dataframe
df = Harness(
data=iris['data'], index=Categorical(iris['target']),
estimator=discriminant_analysis.LinearDiscrimin... |
2,232 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Bayesian interpretation of medical tests
This notebooks explores several problems related to interpreting the results of medical tests.
Copyright 2016 Allen Downey
MIT License
Step3: Medica... | Python Code:
from __future__ import print_function, division
from thinkbayes2 import Pmf, Suite
from fractions import Fraction
Explanation: Bayesian interpretation of medical tests
This notebooks explores several problems related to interpreting the results of medical tests.
Copyright 2016 Allen Downey
MIT License: htt... |
2,233 | 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... |
2,234 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Implementation of ADAM
This method computes individual adaptive learning rates for different parameters from estimates of first and second moments of the gradients; the name Adam is derived ... | Python Code:
%matplotlib inline
import numpy as np
import math
import matplotlib.pyplot as plt
Explanation: Implementation of ADAM
This method computes individual adaptive learning rates for different parameters from estimates of first and second moments of the gradients; the name Adam is derived from adaptive moment e... |
2,235 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Ocean
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specify d... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'nasa-giss', 'sandbox-2', 'ocean')
Explanation: ES-DOC CMIP6 Model Properties - Ocean
MIP Era: CMIP6
Institute: NASA-GISS
Source ID: SANDBOX-2
Topic: Ocean
Sub-Topics: Timestepping Fra... |
2,236 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Regression Week 4
Step1: Load in house sales data
Dataset is from house sales in King County, the region where the city of Seattle, WA is located.
Step2: If we want to do any "feature engi... | Python Code:
import graphlab
import numpy as np
Explanation: Regression Week 4: Ridge Regression (gradient descent)
In this notebook, you will implement ridge regression via gradient descent. You will:
* Convert an SFrame into a Numpy array
* Write a Numpy function to compute the derivative of the regression weights wi... |
2,237 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Postcards of Parliament From A Digital Flâneur
Flâneur, noun, A man who saunters around observing society.
The flâneur wandered in the shopping arcades, but he did not give in to the temptat... | Python Code:
import mnis
import datetime
# Create a date for the analysis
d = datetime.date.today()
# Download the full data for MPs serving on the given date as a list
mnis.getCommonsMembersOn(d)[0]
Explanation: Postcards of Parliament From A Digital Flâneur
Flâneur, noun, A man who saunters around observing society.
... |
2,238 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
----- IMPORTANT ------
The code presented here assumes that you're running TensorFlow v1.3.0 or higher, this was not released yet so the easiet way to run this is update your TensorFlow ver... | Python Code:
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import collections
# tensorflow
import tensorflow as tf
print('Expected TensorFlow version is v1.3.0 or higher')
print('Your TensorFlow version:', tf.__version__)
# data manipulation
import numpy as... |
2,239 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Baxter kinematics
In this notebook, we'll try IKPy on the baxter robot
You will get the following chains
Step1: ## Robot import and setup
Step2: Inverse kinematics | Python Code:
# Some necessary imports
import numpy as np
from ikpy.chain import Chain
from ikpy.utils import plot
# Optional: support for 3D plotting in the NB
%matplotlib widget
# turn this off, if you don't need it
Explanation: Baxter kinematics
In this notebook, we'll try IKPy on the baxter robot
You will get the fo... |
2,240 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Time dependent Schrödinger equation
We want to describe an electron wavefunction by a wavepacket
$\psi (x,y)$ that is a function of position $x$ and time $t$. We assume
that the electron is ... | Python Code:
%matplotlib inline
import numpy as np
from matplotlib import pyplot
import math
import matplotlib.animation as animation
from IPython.display import HTML
lx=20
dx = 0.04
nx = int(lx/dx)
dt = dx**2/20.
V0 = 60
alpha = dt/dx**2
fig = pyplot.figure()
ax = pyplot.axes(xlim=(0, lx), ylim=(0, 2), xlabel='x', yla... |
2,241 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
OpenTire Moment Method Example
Draws a constant velocity force-moment diagram of a bicycle using the OpenTire library
Import OpenTire and other libraries used in this demonstration
Step1: D... | Python Code:
from opentire import OpenTire
from opentire.Core import TireState
import numpy as np
import matplotlib.pyplot as plt
Explanation: OpenTire Moment Method Example
Draws a constant velocity force-moment diagram of a bicycle using the OpenTire library
Import OpenTire and other libraries used in this demonstrat... |
2,242 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Parte III
Step1: 2. Entrenando un primer modelo (IV)
Step2: 2. Entrenando un primer modelo (V)
En este primer ejemplo ignoramos muchas cuestiones que se tienen que tomar en cuenta en proye... | Python Code:
# configuramos matplotlib para incluir las gráficas en jupyter e importamos pandas
%matplotlib inline
import pandas as pd
# cargamos los datos en un data frame de pandas
url = 'http://mlr.cs.umass.edu/ml/machine-learning-databases/iris/iris.data'
names = ['sepal_length', 'sepal_width', 'petal_length', 'pet... |
2,243 | 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="#Calibrated-Recommendations" data-toc-modified-id="Calibrated-Recommendations... | Python Code:
# code for loading the format for the notebook
import os
# path : store the current path to convert back to it later
path = os.getcwd()
os.chdir(os.path.join('..', '..', 'notebook_format'))
from formats import load_style
load_style(css_style='custom2.css', plot_style=False)
os.chdir(path)
# 1. magic for in... |
2,244 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction
The Lines object provides the following features
Step1: Basic Line Chart
Step2: We can explore the different attributes by changing each of them for the plot above
Step3: In ... | Python Code:
import numpy as np
from pandas import date_range
import bqplot.pyplot as plt
from bqplot import *
security_1 = np.cumsum(np.random.randn(150)) + 100.
security_2 = np.cumsum(np.random.randn(150)) + 100.
Explanation: Introduction
The Lines object provides the following features:
Ability to plot a single set ... |
2,245 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Zipline beginner tutorial
Basics
Zipline is an open-source algorithmic trading simulator written in Python.
The source can be found at
Step1: As you can see, we first have to import some fu... | Python Code:
# assuming you're running this notebook in zipline/docs/notebooks
import os
if os.name == 'nt':
# windows doesn't have the cat command, but uses 'type' similarly
! type "..\..\zipline\examples\buyapple.py"
else:
! cat ../../zipline/examples/buyapple.py
Explanation: Zipline beginner tutorial
Bas... |
2,246 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
TensorFlow Tutorial
Welcome to this week's programming assignment. Until now, you've always used numpy to build neural networks. Now we will step you through a deep learning framework that w... | Python Code:
import math
import numpy as np
import h5py
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow.python.framework import ops
from tf_utils import load_dataset, random_mini_batches, convert_to_one_hot, predict
%matplotlib inline
np.random.seed(1)
Explanation: TensorFlow Tutorial
Welcome to... |
2,247 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Software Engineering for Data Scientists
Manipulating Data with Python
CSE 583
Today's Objectives
1. Opening & Navigating the Jupyter Notebook
2. Simple Math in the Jupyter Notebook
3. Loadi... | Python Code:
!ls
Explanation: Software Engineering for Data Scientists
Manipulating Data with Python
CSE 583
Today's Objectives
1. Opening & Navigating the Jupyter Notebook
2. Simple Math in the Jupyter Notebook
3. Loading data with pandas
4. Cleaning and Manipulating data with pandas
5. Visualizing data with pandas & ... |
2,248 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: 정형 데이터 다루기
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: 판다스로 데이터프레임 만들기
판다스는 정형 데이터를 읽고 ... | 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... |
2,249 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercises
Step1: Data
Step2: Exercise 1
Step3: Exercise 2
Step4: Exercise 3
Step5: Exercise 4 | Python Code:
# Useful Libraries
import numpy as np
import matplotlib.pyplot as plt
from scipy import stats
import seaborn as sns
# Useful functions
def normal_test(X):
z, pval = stats.normaltest(X)
if pval < 0.05:
print 'Values are not normally distributed.'
else:
print 'Values are normall... |
2,250 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using Ray for Highly Parallelizable Tasks
While Ray can be used for very complex parallelization tasks,
often we just want to do something simple in parallel.
For example, we may have 100,00... | Python Code:
import ray
import random
import time
import math
from fractions import Fraction
# Let's start Ray
ray.init(address='auto')
Explanation: Using Ray for Highly Parallelizable Tasks
While Ray can be used for very complex parallelization tasks,
often we just want to do something simple in parallel.
For example,... |
2,251 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: Transfer Learning Using Pretrained ConvNets
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: ... | 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... |
2,252 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Why Version Control?
Here's why.
Step1: If that hasn't convinced you, here are some other benefits | Python Code:
from IPython.display import Image
Image(url='http://www.phdcomics.com/comics/archive/phd101212s.gif')
Explanation: Why Version Control?
Here's why.
End of explanation
%%bash
git status
Explanation: If that hasn't convinced you, here are some other benefits:
http://stackoverflow.com/questions/1408450/why-sh... |
2,253 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
ES-DOC CMIP6 Model Properties - Toplevel
MIP Era
Step1: Document Authors
Set document authors
Step2: Document Contributors
Specify document contributors
Step3: Document Publication
Specif... | Python Code:
# DO NOT EDIT !
from pyesdoc.ipython.model_topic import NotebookOutput
# DO NOT EDIT !
DOC = NotebookOutput('cmip6', 'messy-consortium', 'emac-2-53-vol', 'toplevel')
Explanation: ES-DOC CMIP6 Model Properties - Toplevel
MIP Era: CMIP6
Institute: MESSY-CONSORTIUM
Source ID: EMAC-2-53-VOL
Sub-Topics: R... |
2,254 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
This example builds HMM and MSMs on the alanine_dipeptide dataset using varing lag times
and numbers of states, and compares the relaxation timescales
Step1: First
Step2: Now sequences is ... | Python Code:
from __future__ import print_function
import os
%matplotlib inline
from matplotlib.pyplot import *
from msmbuilder.featurizer import SuperposeFeaturizer
from msmbuilder.example_datasets import AlanineDipeptide
from msmbuilder.hmm import GaussianFusionHMM
from msmbuilder.cluster import KCenters
from msmbuil... |
2,255 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
An Introduction to pandas
Pandas! They are adorable animals. You might think they are the worst animal ever but that is not true. You might sometimes think pandas is the worst library every,... | Python Code:
# import pandas, but call it pd. Why? Because that's What People Do.
import pandas as pd #so that you don't have to type pandas later -- most people use pd instead of pands
Explanation: An Introduction to pandas
Pandas! They are adorable animals. You might think they are the worst animal ever but that is n... |
2,256 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Deep Learning
Assignment 3
Previously in 2_fullyconnected.ipynb, you trained a logistic regression and a neural network model.
The goal of this assignment is to explore regularization techni... | Python Code:
# These are all the modules we'll be using later. Make sure you can import them
# before proceeding further.
from __future__ import print_function
import numpy as np
import tensorflow as tf
from six.moves import cPickle as pickle
Explanation: Deep Learning
Assignment 3
Previously in 2_fullyconnected.ipynb,... |
2,257 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a network written with ... | Python Code:
import pandas as pd
import numpy as np
import tensorflow as tf
import tflearn
from tflearn.data_utils import to_categorical
Explanation: Sentiment analysis with TFLearn
In this notebook, we'll continue Andrew Trask's work by building a network for sentiment analysis on the movie review data. Instead of a n... |
2,258 | 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... |
2,259 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Analyzing the NYC Subway Dataset
Section 1. Statistical Test
1.1 Which statistical test did you use to analyze the NYC subway data? Did you use a one-tail or a two-tail P value? What is the ... | Python Code:
print ggplot(turnstile_weather, aes(x='ENTRIESn_hourly')) +\
geom_histogram(binwidth=1000,position="identity") +\
scale_x_continuous(breaks=range(0, 60001, 10000), labels = range(0, 60001, 10000))+\
facet_grid("rain")+\
ggtitle('Distribution of ENTRIESn_hourly in non-rainy days (0.0) and ra... |
2,260 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Samples and Results
Setup
Step1: Connection
s is a Session object representing a connection to the Ovation API
Step2: Organization id required for all calls.
Step3: Workflow samples
Colle... | Python Code:
import uuid
from pprint import pprint
from datetime import date
from ovation.session import connect_lab
Explanation: Samples and Results
Setup
End of explanation
s = connect_lab(input("Email: "), api='https://lab-services-staging.ovation.io')
Explanation: Connection
s is a Session object representing a con... |
2,261 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Getting data from database
I set up a Postgres database on Amazon Web Services and used a pandasql engine to write SQL queries directly from Python. sqlalchemy_conn is script containing the ... | Python Code:
query = 'SELECT DISTINCT targetname FROM undata WHERE goalid = 1'
targets1 = pd.read_sql(query, engine)
for target in targets1['targetname']:
print target
query = 'SELECT DISTINCT targetname FROM undata WHERE goalid = 5'
targets5 = pd.read_sql(query, engine)
for target in targets5['targetname']:
... |
2,262 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Using custom containers with AI Platform Training
Learning Objectives
Step1: Configure environment settings
Set location paths, connections strings, and other environment settings. Make sur... | Python Code:
import json
import os
import pickle
import tempfile
import time
import uuid
from typing import NamedTuple
import numpy as np
import pandas as pd
from google.cloud import bigquery
from googleapiclient import discovery, errors
from jinja2 import Template
from kfp.components import func_to_container_op
from s... |
2,263 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Exercise from Think Stats, 2nd Edition (thinkstats2.com)<br>
Allen Downey
Read the pregnancy file.
Step1: Select live births, then make a CDF of <tt>totalwgt_lb</tt>.
Step2: Display the CD... | Python Code:
%matplotlib inline
import nsfg
preg = nsfg.ReadFemPreg()
import thinkstats2
import thinkplot
import numpy as np
Explanation: Exercise from Think Stats, 2nd Edition (thinkstats2.com)<br>
Allen Downey
Read the pregnancy file.
End of explanation
live = preg[preg.outcome == 1]
print live
wgt_cdf = thinkstats2.... |
2,264 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Welcome to the Echo package
The "echo" subpackage of murraylab_tools is designed to automate the setup of reactions (mostly TX-TL reactions) with the Echo. The EchoRun class can produce pick... | Python Code:
import murraylab_tools.echo as mt_echo
import os.path
# Relevant input and output files. Check these out for examples of input file format.
txtl_inputs = os.path.join("txtl_setup", "inputs")
txtl_outputs = os.path.join("txtl_setup", "outputs")
stock_file = os.path.join(txtl_inputs, "TX-TL_setup_example_s... |
2,265 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
1A.algo - La sous-séquence de plus grande somme
Ce problème est connu sur le nom de Maximum subarray problem. Notion abordée
Step1: Enoncé
On suppose qu'on a une liste $L=( l_1, l_2, ..., ... | Python Code:
%matplotlib inline
from jyquickhelper import add_notebook_menu
add_notebook_menu()
Explanation: 1A.algo - La sous-séquence de plus grande somme
Ce problème est connu sur le nom de Maximum subarray problem. Notion abordée : programmation dynamique.
End of explanation
def somme_partielle(li, i, j):
r = 0... |
2,266 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Data
Step2: Constant baseline
As a baseline, we use the empirical mean of y.
Step3: Kernel regression
Step4: We can visualize the kernel matrix to see which inputs ... | Python Code:
import numpy as np
import matplotlib.pyplot as plt
np.random.seed(seed=1)
import math
import collections
try:
import torch
except ModuleNotFoundError:
%pip install -qq torch
import torch
from torch import nn
from torch.nn import functional as F
try:
from probml_utils import d2l
except Modul... |
2,267 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2018 The TensorFlow Authors.
Step1: Rock, Paper & Scissors with TensorFlow Hub - TFLite
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https... | Python Code:
#@title Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# dist... |
2,268 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Video Segments
The following example shows how to read the video segments files
Step1: The duration of the segments has to be defined manually. It is 5s for all provided video segment files... | Python Code:
import numpy as np
import pandas as pd
import matplotlib.pylab as plt
dfsegs = pd.read_csv("../data/videos/CRZbG73SX3s_segments.csv")
Explanation: Video Segments
The following example shows how to read the video segments files:
End of explanation
segment_duration = 5
Explanation: The duration of the segmen... |
2,269 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href="https
Step1: Processing Robotic total station data
Upload total station data into sample_data folder
Unfortunately, in the space delimited text file, there are spaces in the time ... | Python Code:
import re # for regular expressions
import numpy as np # for vector/matri operations
import matplotlib.pyplot as plt # for charts
import pandas as pd # for table like data structures
from datetime import datetime, timedelta # for time/date handling
Ex... |
2,270 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
CAPM - Capital Asset Pricing Model
Watch the video for the full overview.
Portfolio Returns
Step1: Compare Cumulative Return
Step2: Get Daily Return
Step3: What if our stock was completel... | Python Code:
# Model CAPM as a simple linear regression
from scipy import stats
help(stats.linregress)
import pandas as pd
import pandas_datareader as web
spy_etf = web.DataReader('SPY', 'google')
spy_etf.info()
spy_etf.head()
start = pd.to_datetime('2010-01-04')
end = pd.to_datetime('2017-07-18')
aapl = web.DataReader... |
2,271 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Measuring a Multiport Device with a 2-Port Network Analyzer
Introduction
In microwave measurements, one commonly needs to measure a n-port device with a m-port network analyzer ($m<n$ of cou... | Python Code:
import skrf as rf
from itertools import combinations
%matplotlib inline
from pylab import *
rf.stylely()
Explanation: Measuring a Multiport Device with a 2-Port Network Analyzer
Introduction
In microwave measurements, one commonly needs to measure a n-port device with a m-port network analyzer ($m<n$ of c... |
2,272 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<a href='http
Step1: Concatenation
Concatenation basically glues together DataFrames. Keep in mind that dimensions should match along the axis you are concatenating on. You can use pd.conca... | Python Code:
import pandas as pd
df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
'B': ['B0', 'B1', 'B2', 'B3'],
'C': ['C0', 'C1', 'C2', 'C3'],
'D': ['D0', 'D1', 'D2', 'D3']},
index=[0, 1, 2, 3])
df2 = pd.DataFrame({'A': [... |
2,273 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Plane-DEM intersections
First dated version
Step1: Test case 1
The first test case is illustrated in the image below. We have a horizontal topographic surface, at a height of 0, with 100 x ... | Python Code:
from pygsf.io.gdal.raster import try_read_raster_band
Explanation: Plane-DEM intersections
First dated version: 2019-06-11
Current version: 2021-04-24
Last run: 2021-04-24
A few simulated topographic surfaces were used to validate the routine for calculating the plane-DEM intersection.
Loading the dataset ... |
2,274 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Scores (pyannote.core.scores.Scores)
Step1: Scores instances are used to describe classification scores.
For instance, one can use a Scores to store the result of speaker identification app... | Python Code:
from pyannote.core import Scores
Explanation: Scores (pyannote.core.scores.Scores)
End of explanation
scores = Scores(
uri='TheBigBangTheory.Season01.Episode01',
modality='speaker'
)
Explanation: Scores instances are used to describe classification scores.
For instance, one can use a Scores to sto... |
2,275 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
analyzing data from multiple files
software carpentry
Step1: if / else statements
syntax similar to that in loops, need
Step2: useful tools for strings
Step3: regular expressions
We have... | Python Code:
import glob
glob.glob("inflammation-??.csv")
filenames = glob.glob('inflammation*.csv')
for f in filenames:
data = numpy.loadtxt(fname=f, delimiter=',')
print("file",f[13:15],
", # rows and columns: ", data.shape, sep="")
import numpy
import matplotlib.pyplot
filenames = sorted(glob.glob(... |
2,276 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Loan Approval Model
Created with H2O Automatic Machine Learning
This notebook ingests a dataset, and trains many machine learning models intelligently searching the hyper-parameter space for... | Python Code:
%%capture
import h2o
from h2o.automl import H2OAutoML
import os
import plotly
import cufflinks
import plotly.plotly as py
import plotly.graph_objs as go
import plotly.figure_factory as ff
plotly.offline.init_notebook_mode(connected=True)
myPlotlyKey = os.environ['SECRET_ENV_BRETTS_PLOTLY_KEY']
py.sign_in(u... |
2,277 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
13 Boucles for et while
Step1: 13.1 La boucle for
Syntaxe
Step2: 13.4 Mise à jour d'une variable
Step3: 13.5 Quelques exemples
Calculer la somme des éléments d'une liste
Step4: Écri... | Python Code:
from IPython.display import Image
Image('../NotesDeCours/images/bart_simpson.jpg')
range(100, 109)
for i in range(100, 109):
print(i, "I will not do this again")
for i in range(10):
print(i)
Explanation: 13 Boucles for et while
End of explanation
s = 0
Explanation: 13.1 La boucle for
Syntaxe :
for ... |
2,278 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Fitting a linear model fp1
Step1: Linear Function
Step2: Fitting the model with polynomial degree of 2
Step3: Trying to fir the model with 53 polynomial
Step4: As we can see that betwee... | Python Code:
# starting with linear model where degree is 1
# polyfit() - best put that line into the chart so that it results in the smallest
# approximation error
fp1, residuals, rank, sv, rcond = sp.polyfit(X, y, 1, full=True)
fp1
Explanation: Fitting a linear model fp1
End of explanation
print(residuals)
print(rank... |
2,279 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Step1: Image Classification
In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. You'll preprocess the images... | Python Code:
DON'T MODIFY ANYTHING IN THIS CELL THAT IS BELOW THIS LINE
from urllib.request import urlretrieve
from os.path import isfile, isdir
from tqdm import tqdm
import problem_unittests as tests
import tarfile
cifar10_dataset_folder_path = 'cifar-10-batches-py'
class DLProgress(tqdm):
last_block = 0
def h... |
2,280 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2019 The TensorFlow Authors.
Step1: Better performance with the tf.data API
<table class="tfo-notebook-buttons" align="left">
<td>
<a target="_blank" href="https
Step2: Thr... | 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... |
2,281 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Cat vs coherent states in a Kerr resonator, and the role of measurement
$\newcommand{\ket}[1]{| #1 \rangle}$
$\newcommand{\bra}[1]{\langle #1 |}$
$\newcommand{\braket}[1]{\langle #1 \rangle}... | Python Code:
import matplotlib.pyplot as plt
import numpy as np
from qutip import *
from IPython.display import display, Math, Latex
Explanation: Cat vs coherent states in a Kerr resonator, and the role of measurement
$\newcommand{\ket}[1]{| #1 \rangle}$
$\newcommand{\bra}[1]{\langle #1 |}$
$\newcommand{\braket}[1]{\la... |
2,282 |
Given the following text problem statement, write Python code to implement the functionality described below in problem statement
Problem:
Scale Data Using Standard Scaler in Sklearn
| Python Code::
from sklearn.preprocessing import StandardScaler
#Initalise standard scaler
scaler = StandardScaler()
#Fit the scaler using X_train data
scaler.fit(X_train)
#Transform X_train and X_test using the scaler and convert back to DataFrame
X_train = pd.DataFrame(scaler.transform(X_train), columns = X_train.colu... |
2,283 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Introduction to parameter tuning
Hyper-parameters
A machine learning model is a mathematical formula with a number of parameters that are learnt from the data. That is the crux of machine le... | Python Code:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
plt.style.use('fivethirtyeight')
#Read the data
#Read the data
df = pd.read_csv("data/historical_loan.csv")
# refine the data
df.years = df.years.fillna(np.mean(df.years))
# Setup the features and target
X = df.iloc[... |
2,284 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Copyright 2020 The TensorFlow Authors.
Step1: 잘라내기 종합 가이드
<table class="tfo-notebook-buttons" align="left">
<td><a target="_blank" href="https
Step2: 모델 정의하기
전체 모델 잘라내기(순차 및 함수형)
모델 정확성의... | 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... |
2,285 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Train a Simple TensorFlow Lite for Microcontrollers model
This notebook demonstrates the process of training a 2.5 kB model using TensorFlow and converting it for use with TensorFlow Lite fo... | Python Code:
# Define paths to model files
import os
MODELS_DIR = 'models/'
if not os.path.exists(MODELS_DIR):
os.mkdir(MODELS_DIR)
MODEL_TF = MODELS_DIR + 'model'
MODEL_NO_QUANT_TFLITE = MODELS_DIR + 'model_no_quant.tflite'
MODEL_TFLITE = MODELS_DIR + 'model.tflite'
MODEL_TFLITE_MICRO = MODELS_DIR + 'model.cc'
Exp... |
2,286 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<img src='http
Step1: First algorithm
Step2: Note 1
Step3: Representing Cities and Distance
Now for the notion of distance. We define total_distance(tour) as the sum of the distances bet... | Python Code:
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
import random, operator
import time
import itertools
import numpy
import math
%matplotlib inline
random.seed(time.time()) # planting a random seed
Explanation: <img src='http://www.puc-rio.br/sobrepuc/admin/vrd/... |
2,287 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Visualize the Architecture of a Neural Network
Step1: The function $\texttt{generateNN}(\texttt{Topology})$ takes a
network topology Topology as its argument and draws a graph of the
resu... | Python Code:
import graphviz as gv
Explanation: Visualize the Architecture of a Neural Network
End of explanation
def generateNN(Topology):
L = len(Topology)
input_layer = ['i' + str(i) for i in range(1, Topology[0]+1)]
hidden_layers = [['h' + str(k+1) + ',' + str(i) for i in range(1, s+1)]
... |
2,288 | 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 ... |
2,289 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Pull political boundary data from OpenStreetMap as shapefile
This notebook pulls political boundary data from the OpenStreetMap database and creates a shapefile containing the query results.... | Python Code:
bounding_box_file = ""
result_shapefile_filepath = ""
p1 = pyproj.Proj("+init=epsg:31254")
p2 = pyproj.Proj("+init=epsg:4326")
p3 = pyproj.Proj("+init=epsg:3857")
p4 = pyproj.Proj("+init=epsg:25832")
Explanation: Pull political boundary data from OpenStreetMap as shapefile
This notebook pulls political bou... |
2,290 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Learning Scikit-learn
Step1: Let's start again with our text-classification problem, but for now we will only use a reduced number of instances. We will work only with 3,000 instances.
Step... | Python Code:
%pylab inline
import IPython
import sklearn as sk
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
print 'IPython version:', IPython.__version__
print 'numpy version:', np.__version__
print 'scikit-learn version:', sk.__version__
print 'matplotlib version:', matplotlib.__version__
Expla... |
2,291 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Multiple linear regression
Step1: Fitting multiple linear regression to the training set
Step2: Building the optimal model using Backward elimination
Previously to build the multiple regre... | Python Code:
# Import the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
#importing the datset
dataset = pd.read_csv('datasets/50_Startups.csv')
dataset.head()
X = dataset.iloc[:, :-1].values
Y = dataset.iloc[:, 4].values
X
Y
# But there is categorical variable. i.e. independent varaib... |
2,292 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Slice in volumetric data, via Plotly
A volume included in a parallelepiped is described by the values of a scalar field, $f(x,y,z)$, with $x\in[a,b]$, $y\in [c,d]$, $z\in[e,f]$.
A slice in ... | Python Code:
import numpy as np
import plotly.graph_objects as go
from IPython
Explanation: Slice in volumetric data, via Plotly
A volume included in a parallelepiped is described by the values of a scalar field, $f(x,y,z)$, with $x\in[a,b]$, $y\in [c,d]$, $z\in[e,f]$.
A slice in this volume is visualized by coloring ... |
2,293 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
회귀 분석용 가상 데이터 생성 방법
Scikit-learn 의 datasets 서브 패키지에는 회귀 분석 시험용 가상 데이터를 생성하는 명령어인 make_regression() 이 있다.
http
Step1: 위 선형 모형은 다음과 같다.
$$
y = 100 + 79.1725 x
$$
noise 인수를 증가시키면 $\text{Var}... | Python Code:
from sklearn.datasets import make_regression
X, y, c = make_regression(n_samples=10, n_features=1, bias=0, noise=0, coef=True, random_state=0)
print("X\n", X)
print("y\n", y)
print("c\n", c)
plt.scatter(X, y, s=100)
plt.show()
Explanation: 회귀 분석용 가상 데이터 생성 방법
Scikit-learn 의 datasets 서브 패키지에는 회귀 분석 시험용 가상 데... |
2,294 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<h1 align='center' style="margin-bottom
Step1: Here is a broad outline of technical steps to be done for data collection
Sign up for TMDB (themoviedatabase.org), and set up API to scrape mo... | Python Code:
import torchvision
import urllib2
import requests
import json
import imdb
import time
import itertools
import wget
import os
import tmdbsimple as tmdb
import numpy as np
import random
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
import seaborn as sns
import pickle
Explanation: <h1 a... |
2,295 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Updated TOC trends analysis (part 2)
This notebook begins to explore trends in the broader water chemistry dataset collated by Heleen, Don and John for the updated TOC analysis. Note that th... | Python Code:
# Import custom functions
# Connect to db
resa2_basic_path = (r'C:\Data\James_Work\Staff\Heleen_d_W\ICP_Waters\Upload_Template'
r'\useful_resa2_code.py')
resa2_basic = imp.load_source('useful_resa2_code', resa2_basic_path)
engine, conn = resa2_basic.connect_to_resa2()
# Import code for ... |
2,296 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Vertex client library
Step1: Install the latest GA version of google-cloud-storage library as well.
Step2: Restart the kernel
Once you've installed the Vertex client library and Google clo... | Python Code:
import os
import sys
# Google Cloud Notebook
if os.path.exists("/opt/deeplearning/metadata/env_version"):
USER_FLAG = "--user"
else:
USER_FLAG = ""
! pip3 install -U google-cloud-aiplatform $USER_FLAG
Explanation: Vertex client library: AutoML text entity extraction model for online prediction
<tab... |
2,297 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
Chapter 25
Modeling and Simulation in Python
Copyright 2021 Allen Downey
License
Step1: In the previous chapter we modeled a system with constant angular
velocity.
In this chapter we take t... | Python Code:
# install Pint if necessary
try:
import pint
except ImportError:
!pip install pint
# download modsim.py if necessary
from os.path import exists
filename = 'modsim.py'
if not exists(filename):
from urllib.request import urlretrieve
url = 'https://raw.githubusercontent.com/AllenDowney/ModSim/... |
2,298 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
<div class="clearfix" style="padding
Step1: Advanced usage
Step2: Model fitting process
N.B. Model-fitting is optional.
Fitting the three-state model takes approximately 30 seconds and th... | Python Code:
%matplotlib notebook
from pyrho import *
loadGUI()
Explanation: <div class="clearfix" style="padding: 10px; padding-left: 0px">
<a href="https://github.com/ProjectPyRhO/PyRhO", target="_blank"><img src="https://raw.githubusercontent.com/ProjectPyRhO/Prometheus/master/resources/images/PyRhO_logo_H_crop.png"... |
2,299 | Given the following text description, write Python code to implement the functionality described below step by step
Description:
COVID-19 Моделирование распространения и анализ
Целью данной лабораторной является построение модели заболевания населения COVID-19, обладающей как можно лучшей предсказательной силой. Кажды... | Python Code:
# Устанавливаем библиотеки, если это не было сделано ранее.
# ! pip3 install seaborn matplotlib numpy pandas
# Импорт библиотек
import numpy as np
import matplotlib.pyplot as plt
import urllib.request
import pandas as pd
import seaborn as sns
# Используем настройки seaborn по-умолчанию, устанавливаем тольк... |
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