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Practical Deep Learning - A Python-Based Introduction, 2nd Edition by Ronald T. Kneusel ISBN 9781718504202, 718504209 instant download

  • SKU: EBN-238594620
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Instant download (eBook) Practical Deep Learning - A Python-Based Introduction, 2nd Edition after payment.
Authors:Ronald T. Kneusel
Pages:587 pages
Year:2025
Edition:2
Publisher:No Starch Press
Language:english
File Size:10.35 MB
Format:pdf
ISBNS:9781718504202, 718504209
Categories: Ebooks

Product desciption

Practical Deep Learning - A Python-Based Introduction, 2nd Edition by Ronald T. Kneusel ISBN 9781718504202, 718504209 instant download

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, you’ll 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 you’re 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 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
 
Each chapter emphasizes practical skill development and experimentation, building to a case study that incorporates everything you’ve 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, you’ll 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).
*Free conversion of into popular formats such as PDF, DOCX, DOC, AZW, EPUB, and MOBI after payment.

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