Title: Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines, Author: Chris Fregly
Title: Transformers in Action, Author: Nicole Koenigstein
Title: Causal Inference in Python: Applying Causal Inference in the Tech Industry, Author: Matheus Facure
Title: Pattern Recognition and Machine Learning, Author: Christopher M. Bishop
Title: Essential GraphRAG: Knowledge Graph-Enhanced RAG, Author: Tomaz Bratanic
Title: Hands-On Generative AI with Transformers and Diffusion Models, Author: Omar Sanseviero
Title: Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications, Author: Chris Fregly
Title: Data Governance: The Definitive Guide: People, Processes, and Tools to Operationalize Data Trustworthiness, Author: Evren Eryurek
Title: Prompt Engineering for LLMs: The Art and Science of Building Large Language Model-Based Applications, Author: John Berryman
Title: Hands-On Large Language Models: Language Understanding and Generation, Author: Jay Alammar
Title: Probabilistic Machine Learning: An Introduction, Author: Kevin P. Murphy
Title: Learning TensorFlow.js: Powerful Machine Learning in JavaScript, Author: Gant Laborde
Title: Practical MLOps: Operationalizing Machine Learning Models, Author: Noah Gift
Title: Coding with AI: Examples in Python, Author: Jeremy Morgan
Title: Applied Machine Learning and AI for Engineers: Solve Business Problems That Can't Be Solved Algorithmically, Author: Jeff Prosise
Title: Practical Linear Algebra for Data Science: From Core Concepts to Applications Using Python, Author: Mike X Cohen
Title: Designing Large Language Model Applications: A Holistic Approach to LLMs, Author: Suhas Pai
Title: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Author: Trevor Hastie
Title: Essential Math for AI: Next-Level Mathematics for Efficient and Successful AI Systems, Author: Hala Nelson
Title: LLMs and Generative AI for Healthcare: The Next Frontier, Author: Kerrie Holley

Pagination Links