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Generative AI with Python and PyTorch. Hands-on projects and cutting-edge techniques using generative adversarial networks and LLMs - Second Edition

Język publikacji: angielskim
Autorzy:
Joseph Babcock, Raghav Bali
Generative AI with Python and PyTorch. Hands-on projects and cutting-edge techniques using generative adversarial networks and LLMs - Second Edition Joseph Babcock, Raghav Bali - okladka książki

Generative AI with Python and PyTorch. Hands-on projects and cutting-edge techniques using generative adversarial networks and LLMs - Second Edition Joseph Babcock, Raghav Bali - okladka książki

Serie wydawnicze:
Expert Insight
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Stron:
500
Become an expert in generative AI through practical projects to leverage cutting-edge models for Natural Language Processing (NLP) and computer vision. Generative AI with Python and PyTorch, Second Edition, is your comprehensive guide to creating advanced AI applications. Leveraging Python, this book provides a detailed exploration of the latest generative AI technologies.

From NLP to image generation, this edition dives into practical applications and the underlying theories that enable these technologies. By integrating the latest advancements and applications of large language models, this book prepares you to design and implement powerful AI systems that transform data into actionable insights.

You’ll build your LLM toolbox by learning about various models, tools, and techniques, including GPT-4, LangChain, RLHF, LoRA, and retrieval augmented generation. This deep learning book shows you how to generate images and apply styler transfer using GANs, before implementing CLIP and diffusion models.

Whether you’re creating dynamic content or developing complex AI-driven solutions, Generative AI with Python and PyTorch, Second Edition, equips you with the knowledge to use Python and AI to their full potential.

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O autorach książki

Joseph Babcock has spent almost a decade exploring complex datasets and combining predictive modeling with visualization to understand correlations and forecast anticipated outcomes. He received a PhD from the Solomon H. Snyder Department of Neuroscience at The Johns Hopkins University School of Medicine, where he used machine learning to predict adverse cardiac side effects of drugs. Outside the academy, he has tackled big data challenges in the healthcare and entertainment industries.
Raghav Bali has a master's degree (gold medalist) in information technology from International Institute of Information Technology, Bangalore. He is a data scientist at Intel, the world's largest silicon company, where he works on analytics, business intelligence, and application development to develop scalable machine learning-based solutions. He has worked as an analyst and developer in domains such as ERP, finance, and BI with some of the top companies of the world.

Joseph Babcock, Raghav Bali - pozostałe książki

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