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Moroney L. AI and ML for Coders in Pytorch. A Coder's Guide...2025
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Category:Other Total size: 84.43 MB Added: 2 months ago (2025-07-02 07:19:01)
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Description:
Textbook in PDF format
Eager to learn AI and Machine Learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed.
From computer vision and natural language processing (NLP) to Generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently.
The goal of this book is to prepare you, as a coder, for just thatâitâs accessible enough if you donât fully understand ML yet, and also exposes you to the advanced concepts that will help you go deeper. The aim: to equip you to be an ML and AI developer without needing a PhD!
Gain the confidence to apply AI without needing advanced math or theory expertise
Discover how to build AI models for computer vision, NLP, and sequence modeling with PyTorch
Learn generative AI techniques with Hugging Face Diffusers and Transformers
Who Should Read This Book:
If youâre interested in AI and ML, and you want to get up and running quickly with building models that learn from data, this book is for you. If youâre interested in getting started with common AI and ML conceptsâcomputer vision, natural language processing, sequence modeling, and moreâand want to see how neural networks can be trained to solve problems in these spaces, I think youâll enjoy this book. And if youâve heard all of the hoopla around generative AI, we roll our sleeves up and explore how that works with transformer and diffuser-based models.
Most of all, if youâve put off entering this valuable area of computer science because of perceived difficulty, in particular believing that youâll need to dust off your old calculus books, then fear not: this book takes a code-first approach that shows you just how easy it is to get started in the world of ML and artificial intelligence using PyTorch