Description
Deep learning made simple.
Dip into deep learning without drowning in theory with this fully updated edition of Practical Deep Learning from experienced author and AI expert Ronald T. Kneusel.
After a brief review of basic math and coding principles, youll dive into hands-on experiments and learn to build working models for everything from image analysis to creative writing, and gain a thorough understanding of how each technique works under the hood. Whether youre a developer looking to add AI to your toolkit or a student seeking practical machine learning skills, this book will teach you:
How neural networks work and how theyre 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
Each chapter emphasizes practical skill development and experimentation, building to a case study that incorporates everything youve learned to classify audio recordings. Examples of working code you can easily run and modify are provided, and all code is freely available on GitHub. With Practical Deep Learning, second edition, youll gain the skills and confidence you need to build real AI systems that solve real problems.
New to this edition: 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
Binding Type: Paperback
Publisher: No Starch Press
Published: 07/08/2025
Pages: 584
Weight: 2.2lbs
Size: 9.21h x 7.01w x 1.18d
ISBN: 9781718504202
Language: English
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