- Transformers for Natural Language Processing: Build, train, and fine-tune deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, and GPT-3, 2nd Edition
- Context Engineering for Multi-Agent Systems: Move beyond prompting to build a Context Engine, a transparent architecture of context and reasoning
- Hands-On Explainable AI (XAI) with Python: Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps
- Artificial Intelligence By Example: Develop machine intelligence from scratch using real artificial intelligence use cases
- Building Business-Ready Generative AI Systems: Build Human-Centered Generative AI Systems with Agents, Memory, and LLMs for Enterprise








