Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python, Edition 2

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

Responsible Data Science

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

Transformers for Natural Language Processing: Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more

Statistics for Data Science and Analytics

LLM Engineer's Handbook: Master the art of engineering large language models from concept to production

Analytics and Data Science: Advances in Research and Pedagogy

Building Analytics Teams: Harnessing analytics and artificial intelligence for business improvement

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

What Is Data Science?

The Model Thinker: What You Need to Know to Make Data Work for You

Data Structures and Program Design Using C++

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

Mastering Reinforcement Learning with Python: Build next-generation, self-learning models using reinforcement learning techniques and best practices

Algorithms for Decision Making

Machine Learning with Rust: A practical attempt to explore Rust and its libraries across popular machine learning techniques

Forecasting Time Series Data with Facebook Prophet: Build, improve, and optimize time series forecasting models using the advanced forecasting tool

Building Data Science Teams