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Python Machine Learning Cookbook
Table of Contents
Python Machine Learning Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
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Why Subscribe?
Preface
What this book covers
What you need for this book
Who this book is for
Sections
Getting ready
How to do it…
How it works…
There's more…
See also
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
1. The Realm of Supervised Learning
Introduction
Preprocessing data using different techniques
Getting ready
How to do it…
Mean removal
Scaling
Normalization
Binarization
One Hot Encoding
Label encoding
How to do it…
Building a linear regressor
Getting ready
How to do it…
Computing regression accuracy
Getting ready
How to do it…
Achieving model persistence
How to do it…
Building a ridge regressor
Getting ready
How to do it…
Building a polynomial regressor
Getting ready
How to do it…
Estimating housing prices
Getting ready
How to do it…
Computing the relative importance of features
How to do it…
Estimating bicycle demand distribution
Getting ready
How to do it…
There's more…
2. Constructing a Classifier
Introduction
Building a simple classifier
How to do it…
There's more…
Building a logistic regression classifier
How to do it…
Building a Naive Bayes classifier
How to do it…
Splitting the dataset for training and testing
How to do it…
Evaluating the accuracy using cross-validation
Getting ready…
How to do it…
Visualizing the confusion matrix
How to do it…
Extracting the performance report
How to do it…
Evaluating cars based on their characteristics
Getting ready
How to do it…
Extracting validation curves
How to do it…
Extracting learning curves
How to do it…
Estimating the income bracket
How to do it…
3. Predictive Modeling
Introduction
Building a linear classifier using Support Vector Machine (SVMs)
Getting ready
How to do it…
Building a nonlinear classifier using SVMs
How to do it…
Tackling class imbalance
How to do it…
Extracting confidence measurements
How to do it…
Finding optimal hyperparameters
How to do it…
Building an event predictor
Getting ready
How to do it…
Estimating traffic
Getting ready
How to do it…
4. Clustering with Unsupervised Learning
Introduction
Clustering data using the k-means algorithm
How to do it…
Compressing an image using vector quantization
How to do it…
Building a Mean Shift clustering model
How to do it…
Grouping data using agglomerative clustering
How to do it…
Evaluating the performance of clustering algorithms
How to do it…
Automatically estimating the number of clusters using DBSCAN algorithm
How to do it…
Finding patterns in stock market data
How to do it…
Building a customer segmentation model
How to do it…
5. Building Recommendation Engines
Introduction
Building function compositions for data processing
How to do it…
Building machine learning pipelines
How to do it…
How it works…
Finding the nearest neighbors
How to do it…
Constructing a k-nearest neighbors classifier
How to do it…
How it works…
Constructing a k-nearest neighbors regressor
How to do it…
How it works…
Computing the Euclidean distance score
How to do it…
Computing the Pearson correlation score
How to do it…
Finding similar users in the dataset
How to do it…
Generating movie recommendations
How to do it…
6. Analyzing Text Data
Introduction
Preprocessing data using tokenization
How to do it…
Stemming text data
How to do it…
How it works…
Converting text to its base form using lemmatization
How to do it…
Dividing text using chunking
How to do it…
Building a bag-of-words model
How to do it…
How it works…
Building a text classifier
How to do it…
How it works…
Identifying the gender
How to do it…
Analyzing the sentiment of a sentence
How to do it…
How it works…
Identifying patterns in text using topic modeling
How to do it…
How it works…
7. Speech Recognition
Introduction
Reading and plotting audio data
How to do it…
Transforming audio signals into the frequency domain
How to do it…
Generating audio signals with custom parameters
How to do it…
Synthesizing music
How to do it…
Extracting frequency domain features
How to do it…
Building Hidden Markov Models
How to do it…
Building a speech recognizer
How to do it…
8. Dissecting Time Series and Sequential Data
Introduction
Transforming data into the time series format
How to do it…
Slicing time series data
How to do it…
Operating on time series data
How to do it…
Extracting statistics from time series data
How to do it…
Building Hidden Markov Models for sequential data
Getting ready
How to do it…
Building Conditional Random Fields for sequential text data
Getting ready
How to do it…
Analyzing stock market data using Hidden Markov Models
How to do it…
9. Image Content Analysis
Introduction
Operating on images using OpenCV-Python
How to do it…
Detecting edges
How to do it…
Histogram equalization
How to do it…
Detecting corners
How to do it…
Detecting SIFT feature points
How to do it…
Building a Star feature detector
How to do it…
Creating features using visual codebook and vector quantization
How to do it…
Training an image classifier using Extremely Random Forests
How to do it…
Building an object recognizer
How to do it…
10. Biometric Face Recognition
Introduction
Capturing and processing video from a webcam
How to do it…
Building a face detector using Haar cascades
How to do it…
Building eye and nose detectors
How to do it…
Performing Principal Components Analysis
How to do it…
Performing Kernel Principal Components Analysis
How to do it…
Performing blind source separation
How to do it…
Building a face recognizer using Local Binary Patterns Histogram
How to do it…
11. Deep Neural Networks
Introduction
Building a perceptron
How to do it…
Building a single layer neural network
How to do it…
Building a deep neural network
How to do it…
Creating a vector quantizer
How to do it…
Building a recurrent neural network for sequential data analysis
How to do it…
Visualizing the characters in an optical character recognition database
How to do it…
Building an optical character recognizer using neural networks
How to do it…
12. Visualizing Data
Introduction
Plotting 3D scatter plots
How to do it…
Plotting bubble plots
How to do it…
Animating bubble plots
How to do it…
Drawing pie charts
How to do it…
Plotting date-formatted time series data
How to do it…
Plotting histograms
How to do it…
Visualizing heat maps
How to do it…
Animating dynamic signals
How to do it…
Index
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