Pattern Recognition

Modern Computing

Principles and Paradigms

Securing the Internet of Things

Machine Learning and Beyond

Superintelligence

Paths, Dangers, Strategies

Handbook of Reinforcement Learning

The Laws of Thought

The Quest for a Mathematical Theory of the Mind

HBR Guide to Generative AI for Managers

HBR Guide

Mathematics for Machine Learning

How To Think About AI A Guide For The Perplexed

A Guide For The Perplexed

Think Python 3e

How To Think Like a Computer Scientist

Analytics Engineering with SQL and Dbt

Building Meaningful Data Models at Scale

Learning Data Science

Data Wrangling, Exploration, Visualization, and Modeling with Python

Modern Computing

Principles and Paradigms

Learning AutoML

Automating ML Pipelines with Autogluon, Leading Frameworks, and Real-World Integration

Hands-On Machine Learning with Scikit-Learn and PyTorch

Concepts, Tools, and Techniques to Build Intelligent Systems

Deciphering Data Architectures

Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh

Effective Machine Learning Teams

Best Practices for ML Practitioners

Data Science on AWS

Implementing End-To-End, Continuous AI and Machine Learning Pipelines

Practical Machine Learning for Computer Vision

End-to-End Machine Learning for Images

Learning Algorithms

A Programmer's Guide to Writing Better Code

Beyond Vibe Coding

From Coder to Ai-Era Developer

Machine Learning Strategies and Security Enhancement in Agricultural Sustainability

Superhuman

Beyond the Limits of Our Intelligence

Computational Intelligence in Wired and Wireless Networks

Computational Intelligence in Signal Processing and Automation

Machine Learning Meets Discourse

Algorithms, Performance, and Interpretation