Data Rookies Labs Data Mining with R

Reinforcement Learning in Action

From Foundations to Frontier AI

Reinforcement Learning in Action

From Foundations to Frontier AI

Securing the Internet of Things

Machine Learning and Beyond

Superintelligence

Paths, Dangers, Strategies

Hands-On Machine Learning with Scikit-Learn and PyTorch

Concepts, Tools, and Techniques to Build Intelligent Systems

Handbook of Reinforcement Learning

HBR Guide to Generative AI for Managers

HBR Guide

Analytics Engineering with SQL and Dbt

Building Meaningful Data Models at Scale

Think Python 3e

How To Think Like a Computer Scientist

How To Think About AI A Guide For The Perplexed

A Guide For The Perplexed

Learning Data Science

Data Wrangling, Exploration, Visualization, and Modeling with Python

Learning AutoML

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

Mathematics for Machine Learning

Learning Algorithms

A Programmer's Guide to Writing Better Code

AI Engineering

Building Applications with Foundation Models

The Laws of Thought

The Quest for a Mathematical Theory of the Mind

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

AI

Unexplainable, Unpredictable, Uncontrollable

Practical Machine Learning for Computer Vision

End-to-End Machine Learning for Images

Data Science on AWS

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

A Brief History of Intelligence

Why the Evolution of the Brain Holds the Key to the Future of AI

Building Applications with AI Agents

Designing and Implementing Multi-Agent Systems

Beyond Vibe Coding

From Coder to Ai-Era Developer