Mastering Machine Learning with scikit-learn: Apply effective learning algorithms to real-world problems using scikit-learn

✍ Scribed by Gavin Hackeling

Publisher: Packt Publishing
Year: 2014
Tongue: English
Leaves: 238
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

This book examines machine learning models including logistic regression, decision trees, and support vector machines, and applies them to common problems such as categorizing documents and classifying images. It begins with the fundamentals of machine learning, introducing you to the supervised-unsupervised spectrum, the uses of training and test data, and evaluating models. You will learn how to use generalized linear models in regression problems, as well as solve problems with text and categorical features. You will be acquainted with the use of logistic regression, regularization, and the various loss functions that are used by generalized linear models. The book will also walk you through an example project that prompts you to label the most uncertain training examples. You will also use an unsupervised Hidden Markov Model to predict stock prices.

✦ Subjects

Библиотека;Компьютерная литература;Python;

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