With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. Index : page 393-403
this book is intended to be a fast-paced introduction to various core features of machine learning and deep learning, with code samples that are included in a university course. Index : page 305-319.
This book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. Index : page 811-834.
This book covers the tasks you'll need to perform to keep your databases tuned and performing, and includes new, important innovations with AI Vector Search, JSON Duality Views, and Select AI. Index : page 581-600.
This book The 4th edition brings readers up to date on the latest technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multi agent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI. Appendix : page 1074-1083. Bibliography : page 10…
Notes: page 217-228. Index: page 229-242.