Machine Learning Q and AI (No Starch Press)
Monday, 22 April 2024

This book contains 30 cutting-edge questions and answers on machine learning and AI. Sebastian Raschka goes beyond introductory concepts and digs deeper into machine learning, deep learning, and AI. Stemming from questions often fielded by author Sebastian Raschka, each brief, self-contained chapter journeys through a fundamental question in AI, unraveling it with clear explanations, diagrams, and hands-on exercises.



Author: Sebastian Raschka
Publisher: No Starch Press
Date: April 2024
Pages: 264
ISBN: 978-1718503762
Print: 1718503768
Kindle: B0CKKXCK3T
Audience: developers interested in AI
Level: Intermediate
Category: Artificial Intelligence

Topics include:

  • Manage the various sources of randomness in neural network training
  • Differentiate between encoder and decoder architectures in large language models
  • Reduce overfitting through data and model modifications
  • Construct confidence intervals for classifiers and optimize models with limited labeled data
  • Choose between different multi-GPU training paradigms and different types of generative AI models
  • Understand performance metrics for natural language processing
  • Make sense of the inductive biases in vision transformers

For recommended titles on AI see  AI Books To Inspire You in our Programmer's Bookshelf section.


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Clean Craftsmanship

Author: Robert C. Martin
Publisher: Addison-Wesley
Date: November 2021
Pages: 416
ISBN: 978-0136915713
Print: 013691571X
Audience: General
Rating: 4
Reviewer: Mike James
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Author: Steve Klabnik and Carol Nichols
Publisher: No Starch Press
Date: June 2023
Pages: 560
ISBN: 978-1718503106
Print: 1718503105
Kindle: B0B7QTX8LL
Audience: Systems programmers
Rating: 4.8
Reviewer: Mike James

There's a new edition of what has become the standard text on Rust. Has it matured along with [ ... ]

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