Practical Deep Learning (No Starch Press)
Monday, 15 March 2021

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.

<ASIN:1718500742>

 

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

practdl

 

  • 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.

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Publisher: Apress
Pages: 420
ISBN: 978-1484264904
Print: 1484264908
Kindle: B08TQR3NMF
Audience: SQL Server DBAs and Devs
Rating: 4.5
Reviewer: Ian Stirk

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Publisher: Addison-Wesley Professional
Pages: 464
ISBN: 978-0136886099
Print: 0136886094
Kindle: B094CPJ96B
Audience: Software architects
Rating: 4.5
Reviewer: Kay Ewbank

This is the fourth edition of a book widely regarded as a classic since its firs [ ... ]


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