![]()
Python Machine Learning Cookbook
Table of Contents
Python Machine Learning Cookbook
Credits
About the Author
About the Reviewer
www.PacktPub.com
eBooks, discount offers, and more
Why Subscribe?
Preface
What this book covers
What you need for this book
Who this book is for
Sections
Getting ready
How to do itā¦
How it worksā¦
There's moreā¦
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 itā¦
Mean removal
Scaling
Normalization
Binarization
One Hot Encoding
Label encoding
How to do itā¦
Building a linear regressor
Getting ready
How to do itā¦
Computing regression accuracy
Getting ready
How to do itā¦
Achieving model persistence
How to do itā¦
Building a ridge regressor
Getting ready
How to do itā¦
Building a polynomial regressor
Getting ready
How to do itā¦
Estimating housing prices
Getting ready
How to do itā¦
Computing the relative importance of features
How to do itā¦
Estimating bicycle demand distribution
Getting ready
How to do itā¦
There's moreā¦
2. Constructing a Classifier
Introduction
Building a simple classifier
How to do itā¦
There's moreā¦
Building a logistic regression classifier
How to do itā¦
Building a Naive Bayes classifier
How to do itā¦
Splitting the dataset for training and testing
How to do itā¦
Evaluating the accuracy using cross-validation
Getting readyā¦
How to do itā¦
Visualizing the confusion matrix
How to do itā¦
Extracting the performance report
How to do itā¦
Evaluating cars based on their characteristics
Getting ready
How to do itā¦
Extracting validation curves
How to do itā¦
Extracting learning curves
How to do itā¦
Estimating the income bracket
How to do itā¦
3. Predictive Modeling
Introduction
Building a linear classifier using Support Vector Machine (SVMs)
Getting ready
How to do itā¦
Building a nonlinear classifier using SVMs
How to do itā¦
Tackling class imbalance
How to do itā¦
Extracting confidence measurements
How to do itā¦
Finding optimal hyperparameters
How to do itā¦
Building an event predictor
Getting ready
How to do itā¦
Estimating traffic
Getting ready
How to do itā¦
4. Clustering with Unsupervised Learning
Introduction
Clustering data using the k-means algorithm
How to do itā¦
Compressing an image using vector quantization
How to do itā¦
Building a Mean Shift clustering model
How to do itā¦
Grouping data using agglomerative clustering
How to do itā¦
Evaluating the performance of clustering algorithms
How to do itā¦
Automatically estimating the number of clusters using DBSCAN algorithm
How to do itā¦
Finding patterns in stock market data
How to do itā¦
Building a customer segmentation model
How to do itā¦
5. Building Recommendation Engines
Introduction
Building function compositions for data processing
How to do itā¦
Building machine learning pipelines
How to do itā¦
How it worksā¦
Finding the nearest neighbors
How to do itā¦
Constructing a k-nearest neighbors classifier
How to do itā¦
How it worksā¦
Constructing a k-nearest neighbors regressor
How to do itā¦
How it worksā¦
Computing the Euclidean distance score
How to do itā¦
Computing the Pearson correlation score
How to do itā¦
Finding similar users in the dataset
How to do itā¦
Generating movie recommendations
How to do itā¦
6. Analyzing Text Data
Introduction
Preprocessing data using tokenization
How to do itā¦
Stemming text data
How to do itā¦
How it worksā¦
Converting text to its base form using lemmatization
How to do itā¦
Dividing text using chunking
How to do itā¦
Building a bag-of-words model
How to do itā¦
How it worksā¦
Building a text classifier
How to do itā¦
How it worksā¦
Identifying the gender
How to do itā¦
Analyzing the sentiment of a sentence
How to do itā¦
How it worksā¦
Identifying patterns in text using topic modeling
How to do itā¦
How it worksā¦
7. Speech Recognition
Introduction
Reading and plotting audio data
How to do itā¦
Transforming audio signals into the frequency domain
How to do itā¦
Generating audio signals with custom parameters
How to do itā¦
Synthesizing music
How to do itā¦
Extracting frequency domain features
How to do itā¦
Building Hidden Markov Models
How to do itā¦
Building a speech recognizer
How to do itā¦
8. Dissecting Time Series and Sequential Data
Introduction
Transforming data into the time series format
How to do itā¦
Slicing time series data
How to do itā¦
Operating on time series data
How to do itā¦
Extracting statistics from time series data
How to do itā¦
Building Hidden Markov Models for sequential data
Getting ready
How to do itā¦
Building Conditional Random Fields for sequential text data
Getting ready
How to do itā¦
Analyzing stock market data using Hidden Markov Models
How to do itā¦
9. Image Content Analysis
Introduction
Operating on images using OpenCV-Python
How to do itā¦
Detecting edges
How to do itā¦
Histogram equalization
How to do itā¦
Detecting corners
How to do itā¦
Detecting SIFT feature points
How to do itā¦
Building a Star feature detector
How to do itā¦
Creating features using visual codebook and vector quantization
How to do itā¦
Training an image classifier using Extremely Random Forests
How to do itā¦
Building an object recognizer
How to do itā¦
10. Biometr...