Introduction to Machine Learning with Python

✍ Scribed by Mueller Andreas C., Guido Sarah.

Tongue: English
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Early Release - Raw & Unedited. — O'Really Media, 2016 (September, 25). — 340 p. — ISBN: 1449369413, 978-1-491-91721-3.

Many Python developers are curious about what machine learning is and how it can be concretely applied to solve issues faced in businesses handling medium to large amount of data. Machine Learning with Python teaches you the basics of machine learning and provides a thorough hands-on understanding of the subject.

You’ll learn important machine learning concepts and algorithms, when to use them, and how to use them. The book will cover a machine learning workflow: data preprocessing and working with data, training algorithms, evaluating results, and implementing those algorithms into a production-level system.

Table of Contents:
Introduction.
Supervised Learning.
Unsupervised Learning and Preprocessing.
Summary of scikit-learn methods and usage.
Representing Data and Engineering Features.
Model evaluation and improvement.
Algorithm Chains and Pipelines.
Working with Text Data.

✦ Subjects

Информатика и вычислительная техника;Искусственный интеллект

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