Machine Learning for the Web电子书

Machine Learning for the Web

Table of Contents

Machine Learning for the Web

Credits

Foreword

About the Author

About the Reviewers

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

Conventions

Reader feedback

Customer support

Downloading the example code

Downloading the color images of this book

Errata

Piracy

Questions

1. Introduction to Practical Machine Learning Using Python

General machine-learning concepts

Machine-learning example

Installing and importing a module (library)

Preparing, manipulating and visualizing data – NumPy, pandas and matplotlib tutorials

Using NumPy

Arrays creation

Array manipulations

Array operations

Linear algebra operations

Statistics and mathematical functions

Understanding the pandas module

Exploring data

Manipulate data

Matplotlib tutorial

Scientific libraries used in the book

When to use machine learning

Summary

2. Unsupervised Machine Learning

Clustering algorithms

Distribution methods

Expectation maximization

Mixture of Gaussians

Centroid methods

k-means

Density methods

Mean – shift

Hierarchical methods

Training and comparison of the clustering methods

Dimensionality reduction

Principal Component Analysis (PCA)

PCA example

Singular value decomposition

Summary

3. Supervised Machine Learning

Model error estimation

Generalized linear models

Linear regression

Ridge regression

Lasso regression

Logistic regression

Probabilistic interpretation of generalized linear models

k-nearest neighbours (KNN)

Naive Bayes

Multinomial Naive Bayes

Gaussian Naive Bayes

Decision trees

Support vector machine

Kernel trick

A comparison of methods

Regression problem

Classification problem

Hidden Markov model

A Python example

Summary

4. Web Mining Techniques

Web structure mining

Web crawlers (or spiders)

Indexer

Ranking – PageRank algorithm

Web content mining

Parsing

Natural language processing

Information retrieval models

TF-IDF

Latent Semantic Analysis (LSA)

Doc2Vec (word2vec)

Word2vec – continuous bag of words and skip-gram architectures

Mathematical description of the CBOW model

Doc2Vec extension

Movie review query example

Postprocessing information

Latent Dirichlet allocation

Model

Example

Opinion mining (sentiment analysis)

Summary

5. Recommendation Systems

Utility matrix

Similarities measures

Collaborative Filtering methods

Memory-based Collaborative Filtering

User-based Collaborative Filtering

Item-based Collaborative Filtering

Simplest item-based Collaborative Filtering – slope one

Model-based Collaborative Filtering

Alternative least square (ALS)

Stochastic gradient descent (SGD)

Non-negative matrix factorization (NMF)

Singular value decomposition (SVD)

CBF methods

Item features average method

Regularized linear regression method

Association rules for learning recommendation system

Log-likelihood ratios recommendation system method

Hybrid recommendation systems

Evaluation of the recommendation systems

Root mean square error (RMSE) evaluation

Classification metrics

Summary

6. Getting Started with Django

HTTP – the basics of the GET and POST methods

Installation and server creation

Settings

Writing an app – most important features

Models

URL and views behind HTML web pages

HTML pages

URL declarations and views

Admin

Shell interface

Commands

RESTful application programming interfaces (APIs)

Summary

7. Movie Recommendation System Web Application

Application setup

Models

Commands

User sign up login/logout implementation

Information retrieval system (movies query)

Rating system

Recommendation systems

Admin interface and API

Summary

8. Sentiment Analyser Application for Movie Reviews

Application usage overview

Search engine choice and the application code

Scrapy setup and the application code

Scrapy settings

Scraper

Pipelines

Crawler

Django models

Integrating Django with Scrapy

Commands (sentiment analysis model and delete queries)

Sentiment analysis model loader

Deleting an already performed query

Sentiment reviews analyser – Django views and HTML

PageRank: Django view and the algorithm code

Admin and API

Summary

Index