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Generative AI with Python and PyTorch - Second Edition
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Generative AI with Python and PyTorch
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Overview of this book
Become an expert in Generative AI through immersive, hands-on projects that leverage today’s most powerful models for Natural Language Processing (NLP) and computer vision. Generative AI with Python and PyTorch is your end-to-end guide to creating advanced AI applications, made easy by Raghav Bali, a seasoned data scientist with multiple patents in AI, and Joseph Babcock, a PhD and machine learning expert. Through business-tested approaches, this book simplifies complex GenAI concepts, making learning both accessible and immediately applicable.
From NLP to image generation, this second edition explores practical applications and the underlying theories that power these technologies. By integrating the latest advancements in LLMs, it prepares you to design and implement powerful AI systems that transform data into actionable intelligence.
You’ll build your versatile LLM toolkit by gaining expertise in GPT-4, LangChain, RLHF, LoRA, RAG, and more. You’ll also explore deep learning techniques for image generation and apply styler transfer using GANs, before advancing to implement CLIP and diffusion models.
Whether you’re generating dynamic content or developing complex AI-driven solutions, this book equips you with everything you need to harness the full transformative power of Python and AI.
Table of Contents (18 chapters)
Preface
Introduction to Generative AI: Drawing Data from Models
Building Blocks of Deep Neural Networks
The Rise of Methods for Text Generation
NLP 2.0: Using Transformers to Generate Text
LLM Foundations
Open-Source LLMs
Prompt Engineering
LLM Toolbox
LLM Optimization Techniques
Emerging Applications in Generative AI
Neural Networks Using VAEs
Image Generation with GANs
Style Transfer with GANs
Deepfakes with GANs
Diffusion Models and AI Art
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Index
Customer Reviews