Fundamentals of Deep Learning

Applying Machine Learning in Science Education Research

When, How, and Why?

Deciphering Data Architectures

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

R for Data Science

Import, Tidy, Transform, Visualize, and Model Data

Hands-On Large Language Models

Language Understanding and Generation

Superintelligence

Paths, Dangers, Strategies

Data Governance: The Definitive Guide

People, Processes, and Tools to Operationalize Data Trustworthiness

Building Recommendation Systems in Python and Jax

Hands-On Production Systems at Scale

Analytics Engineering with SQL and Dbt

Building Meaningful Data Models at Scale

Machine Learning with Python Cookbook

2nd Edition - Practical Solutions from Preprocessing to Deep Learning

Prompt Engineering for Generative AI

Future-Proof Inputs for Reliable AI Outputs

Architecting Data and Machine Learning Platforms

Enable Analytics and Ai-Driven Innovation in the Cloud

Causal Inference in Python

Applying Causal Inference in the Tech Industry

Effective Machine Learning Teams

Best Practices for ML Practitioners

Practical Weak Supervision

Doing More with Less Data

Blueprints for Text Analytics using Python

Machine Learning Based Solutions for Common Real World (NLP) Applications

AI-First Healthcare

AI Applications in the Business and Clinical Management of Health

Introducing MLOps

How to Scale Machine Learning in the Enterprise

Modern Data Analytics in Excel

Using Power Query, Power Pivot and More for Enhanced Data Analytics

AI Engineering

Building Applications with Foundation Models

Practical Linear Algebra for Data Science

From Core Concepts to Applications Using Python

Python and R for the Modern Data Scientist

The Best of Both Worlds

Think Bayes

Bayesian Statistics in Python 2nd Edition

Hands-On Generative AI with Transformers and Diffusion Models

Analytical Skills for AI and Data Science

Building Skills for an AI-driven Enterprise