Hands-On Simulation Modeling with Python: Develop simulation models to get accurate results and enhance decision-making processes

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Regression Analysis with R: Design and develop statistical nodes to identify unique relationships within data at scale

Dataclysm: Love, Sex, Race, and Identity--What Our Online Lives Tell Us about Our Offline Selves

Pro Machine Learning Algorithms: A Hands-On Approach to Implementing Algorithms in Python and R

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

Practical Lakehouse Architecture: Designing and Implementing Modern Data Platforms at Scale

Neural Networks with Keras Cookbook: Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots

Deciphering Data Architectures: Choosing Between a Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh

Keras Reinforcement Learning Projects: 9 projects exploring popular reinforcement learning techniques to build self-learning agents

Driving Data Quality with Data Contracts: A comprehensive guide to building reliable, trusted, and effective data platforms

MATLAB for Machine Learning

What Is Data Science?

Keras 2.x Projects: 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras

Effective Amazon Machine Learning

Managing Data as a Product: Design and build data-product-centered socio-technical architectures

Python: Master the Art of Design Patterns

SciPy Recipes: A cookbook with over 110 proven recipes for performing mathematical and scientific computations

Building Data Science Teams

Modern Computer Vision with PyTorch: Explore deep learning concepts and implement over 50 real-world image applications