AI, Machine Learning and Deep Learning 1st Edition

Capture the future of intelligent systems with AI, Machine Learning and Deep Learning — 1st Edition by Fei Hu. This authoritative guide distills complex theory into practical insight, making it an essential read for students, data scientists, engineers, and tech leaders across the US, UK, India, Europe and beyond.

Begin with clear explanations of core concepts — from supervised and unsupervised learning to neural networks and deep architectures — then move into real-world applications that illustrate how algorithms power recommendation systems, computer vision, natural language processing and predictive analytics. The writing balances mathematical rigor with accessible examples, enabling readers to understand both the “why” and the “how.”

Designed for classroom use and professional reference, this edition highlights contemporary methodologies, model evaluation, feature engineering, and deployment considerations relevant to industry and research. Case studies and practical problem-solving scenarios bridge academic learning with deployment challenges faced by teams in Silicon Valley, Bangalore and global AI hubs.

Whether you’re revising fundamentals or exploring advanced architectures, this book offers a smooth learning curve and actionable insights to accelerate your projects and career. Clear diagrams and concise explanations make complex topics approachable without sacrificing depth.

Ready to deepen your expertise in artificial intelligence? Add AI, Machine Learning and Deep Learning (1st Edition) by Fei Hu to your collection today — a smart investment for anyone serious about mastering machine intelligence.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.