R Machine Learning By Example

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

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

Hands-On Transfer Learning with Python: Implement advanced deep learning and neural network models using TensorFlow and Keras

Fundamentals of Data Engineering: Plan and Build Robust Data Systems

R: Unleash Machine Learning Techniques

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

Text Analytics with Python: A Practical Real-World Approach to Gaining Actionable Insights from your Data

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

Generative AI with Python and TensorFlow 2: Create images, text, and music with VAEs, GANs, LSTMs, Transformer models

What Is Data Science?

Generative AI with Python and Pytorch: Navigating the AI Frontier with LLMs, Stable Diffusion, and Next-Gen AI Applications

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

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

Python: Master the Art of Design Patterns

Building Data Science Teams

Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking

Advanced Analytics with Spark: Patterns for Learning from Data at Scale, Edition 2

DATA SCIENCE WITH MYSQL, SQLITE, POSTGRESQL, AND SQL SERVER USING PYTHON GUI

Data Structures and Algorithms