Lecture Notes in Computer Science

Sutskever''s List

Foundational Ideas of Modern AI

Reinforcement Learning Foundations

Handbook of Reinforcement Learning

How We Learn

The New Science of Education and the Brain

Soccer Analytics with Machine Learning

Learning Predictive Modeling Techniques with Sports Data

Superintelligence

Paths, Dangers, Strategies

Python for Excel

A Modern Environment for Automation and Data Analysis

LAWS OF THOUGHT EXAIIE PB

The Quest for a Mathematical Theory of the Mind

Large Language Models - The Hard Part

Open Source AI Solutions for Common Pitfalls

Machine Learning For Dummies

For Dummies (Computer/Tech)

Analytics Engineering with SQL and Dbt

Building Meaningful Data Models at Scale

Learning Data Science

Data Wrangling, Exploration, Visualization, and Modeling with Python

Learning AutoML

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

Architecting Data and Machine Learning Platforms

Enable Analytics and Ai-Driven Innovation in the Cloud

Data Governance: The Definitive Guide

People, Processes, and Tools to Operationalize Data Trustworthiness

Learning Algorithms

A Programmer's Guide to Writing Better Code

High Performance Spark

Best Practices for Scaling and Optimizing Apache Spark

Mathematics for Machine Learning

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

Effective Machine Learning Teams

Best Practices for ML Practitioners

Deciphering Data Architectures

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

HBR Guide to Generative AI for Managers

HBR Guide

Think Python 3e

How To Think Like a Computer Scientist