Title: Machine Learning Production Systems: Engineering Machine Learning Models and Pipelines, Author: Robert Crowe
Title: Developing Apps with GPT-4 and ChatGPT: Build Intelligent Chatbots, Content Generators, and More, Author: Olivier Caelen
Title: Machine Learning Engineering in Action, Author: Ben Wilson
Title: Causal Inference for Data Science, Author: Alex Ruiz de Villa
Title: Architecting Data and Machine Learning Platforms: Enable Analytics and AI-Driven Innovation in the Cloud, Author: Marco Tranquillin
Title: AI and Machine Learning for On-Device Development: A Programmer's Guide, Author: Laurence Moroney
Title: Pattern Recognition and Machine Learning, Author: Christopher M. Bishop
Title: Low-Code AI: A Practical Project-Driven Introduction to Machine Learning, Author: Gwendolyn Stripling
Title: Distributed Machine Learning Patterns, Author: Yuan Tang
Title: Bayesian Reasoning and Machine Learning, Author: David Barber
Title: Hands-On APIs for AI and Data Science: Python Development with FastAPI, Author: Ryan Day
Title: Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow, Author: Hannes Hapke
Title: Distributional Reinforcement Learning, Author: Marc G. Bellemare
Title: Outlier Detection in Python, Author: Brett Kennedy
Title: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems, Author: Aur lien G ron
Title: Data Science: The Hard Parts: Techniques for Excelling at Data Science, Author: Daniel Vaughan
Title: Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions, Author: Michael Munn
Title: Kernel Methods for Pattern Analysis, Author: John Shawe-Taylor
Title: Toward Human-Level Artificial Intelligence: How Neuroscience Can Inform the Pursuit of Artificial General Intelligence or General AI, Author: Eitan Michael Azoff
Title: Machine Learning Algorithms in Depth, Author: Vadim Smolyakov

Pagination Links