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Generative AI with Python and PyTorch. Navigating the AI frontier with LLMs, Stable Diffusion, and next-gen AI applications - Second Edition Joseph Babcock, Raghav Bali

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Generative AI with Python and PyTorch. Navigating the AI frontier with LLMs, Stable Diffusion, and next-gen AI applications  - Second Edition Joseph Babcock, Raghav Bali - okladka książki

Generative AI with Python and PyTorch. Navigating the AI frontier with LLMs, Stable Diffusion, and next-gen AI applications  - Second Edition Joseph Babcock, Raghav Bali - okladka książki

Autorzy:
Joseph Babcock, Raghav Bali
Serie wydawnicze:
Expert Insight
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
450
Dostępne formaty:
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     ePub

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Do przechowalni

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.

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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.

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