Subtitled "A Python Introduction", this book shows how to build working models for tasks from image analysis to creative writing using Python. Ronald T. Kneusel emphasizes practical skill development and experimentation, building to a case study that incorporates everything covered so far to classify audio recordings. Examples of working code you can easily run and modify are provided, and all code is freely available on GitHub.

<ASIN:1718504209 >

This fully revised second edition adds material on computer vision, fine-tuning and transfer learning, localization, self-supervised learning, generative AI for novel image creation, and large language models for in-context learning, semantic search, and retrieval-augmented generation (RAG).

Author: Ronald T. Kneusel
Publisher: No Starch
Date: July 2025
Pages: 584
ISBN: 978-1718504202
Print: 1718504209
Kindle: B0DJQ9NKSG
Audience: Developers interested in AI
Level: Introductory/Intermediate
Category: Artificial Intelligence

Topics include:

• How neural networks work and how they’re trained
• How to use classical machine learning models
• How to develop a deep learning model from scratch
• How to evaluate models with industry-standard metrics
• How to create your own generative AI models

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