Denis Rothman grāmatas
Transformers for Natural Language Processing and Computer Vision - Third Edition: Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3
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Context Engineering for Multi-Agent Systems: Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning
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Artificial Intelligence By Example: Develop machine intelligence from scratch using real artificial intelligence use cases
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Artificial Intelligence By Example - Second Edition
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Hands-On Explainable AI (XAI) with Python: Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps
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Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more
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Transformers for Natural Language Processing - Second Edition: Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAIs GPT-3, ChatGPT, and GPT-4
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RAG-Driven Generative AI: Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone
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Building Business-Ready Generative AI Systems: Build Human-Centered AI Systems with Context Engineering, Agents, Memory, and LLMs for Enterprise
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Context Engineering for Multi-Agent Systems: Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning
-30% ar kodu BOOKS
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RAG-Driven Generative AI - Second Edition: Build MAS-RAG with DualRAG, GraphRAG, multimodal video pipelines, and Oracle Database 23ai
-30% ar kodu BOOKS
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