As its subtitle states, this is a Python-Based Introduction which is aimed at developers curious about machine learning but who don't know where to start. Ron Kneusel focuses on the subfield of machine learning known as deep learning and explains core concept to provide the foundation to start building your own models. After an introduction to Python, the author moves through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance.

Author: Ron Kneusel
Publisher: No Starch Press
Date: February 2021
Pages: 464
ISBN: 978-1718500747
Print: 1718500742
Kindle: B085BVZ9CK
Audience: people interested in deep learning techniques.
Level: Introductory/Intermediate
Category: Artificial Intelligence

• How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines
• How neural networks work and how they’re trained
• How to use convolutional neural networks
• How to develop a successful deep learning model from scratch

For recommendations of Artificial Intelligence books see AI Books To Inspire You in our Programmer's Bookshelf section.

For more Book Watch just click.

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

To have new titles included in Book Watch contact  BookWatch@i-programmer.info

Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.