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Books like Probabilistic Machine Learning An Introduction

What to read after Probabilistic Machine Learning An Introduction by Kevin P. Murphy: 24 titles sharing themes of Machine Learning, Data Science, Artificial Intelligence, and Computer Science, chosen for mood and literary overlap.

Machine Learning Data Science Artificial Intelligence Computer Science Computers

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A diverse selection of titles that share the core themes and atmosphere of Probabilistic Machine Learning An Introduction.

Learning AI Tools in Tableau Level Up Your Data Analytics and Visualization Capabilities with Tableau Pulse and Tableau Agent — Ann Jackson

Learning AI Tools in Tableau Level Up Your Data Analytics and Visualization Capabilities with Tableau Pulse and Tableau Agent

Themes: Machine Learning • Data Science • Artificial Intelligence

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Imitation in Animals and Artifacts

Chrystopher L. Nehaniv

Themes: Machine Learning • Data Science • Artificial Intelligence

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Translational Application of Artificial Intelligence in Healthcare – a Textbook

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Foundation, Architecture and Prototyping of Humanized AI A New Constructivist Approach

Themes: Machine Learning • Data Science • Artificial Intelligence

Machine Learning Methods in the Environmental Sciences Neural Networks and Kernels — William W. Hsieh

Machine Learning Methods in the Environmental Sciences Neural Networks and Kernels

William W. Hsieh

Themes: Machine Learning • Data Science • Artificial Intelligence

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Practical MLOps Operationalizing Machine Learning Models

Themes: Machine Learning • Data Science • Artificial Intelligence

Artificial Intelligence for Business Understand Neural Networks and Machine Learning for Robotics. A Step-By-Step Method to Develop AI and Ml Projects for Business — David Brown

Artificial Intelligence for Business Understand Neural Networks and Machine Learning for Robotics. A Step-By-Step Method to Develop AI and Ml Projects for Business

Themes: Machine Learning • Data Science • Artificial Intelligence

How Smart Machines Think — Sean Gerrish

How Smart Machines Think

Themes: Machine Learning • Data Science • Artificial Intelligence

Deep Learning — Ian Goodfellow

Themes: Machine Learning • Data Science • Artificial Intelligence

Reinforcement Learning Industrial Applications of Intelligent Agents — Phil Winder

Reinforcement Learning Industrial Applications of Intelligent Agents

Themes: Machine Learning • Data Science • Artificial Intelligence

Multifaceted Approaches for Data Acquisition Processing and Communication — Chinmay Chakraborty

Multifaceted Approaches for Data Acquisition Processing and Communication

Chinmay Chakraborty

Themes: Machine Learning • Data Science • Artificial Intelligence

Turing’s Vision How AI Is Shaping the World — Pietro Perconti

Turing’s Vision How AI Is Shaping the World

Pietro Perconti

Themes: Machine Learning • Data Science • Artificial Intelligence

A Concise Introduction to Machine Learning — A. C Faul

A Concise Introduction to Machine Learning

Themes: Machine Learning • Data Science • Artificial Intelligence

Machine Learning for Hackers — Conway, Drew

Machine Learning for Hackers

Themes: Machine Learning • Data Science • Artificial Intelligence

Natural Language Processing with Transformers Building Language Applications with Hugging Face — Lewis Tunstall

Natural Language Processing with Transformers Building Language Applications with Hugging Face

Themes: Machine Learning • Data Science • Artificial Intelligence

In Order to Learn How the Sequence of Topics Influences Learning — Frank E. Ritter

In Order to Learn How the Sequence of Topics Influences Learning

Frank E. Ritter

Themes: Machine Learning • Data Science • Artificial Intelligence

AI Engineering Building Applications with Foundation Models — Chip Huyen

AI Engineering Building Applications with Foundation Models

Themes: Machine Learning • Data Science • Artificial Intelligence

Building Recommendation Systems in Python and Jax Hands-On Production Systems at Scale — Bryan Bischof

Building Recommendation Systems in Python and Jax Hands-On Production Systems at Scale

Themes: Machine Learning • Data Science • Artificial Intelligence

The Elements of Statistical Learning Data Mining, Inference, and Prediction — Trevor Hastie

The Elements of Statistical Learning Data Mining, Inference, and Prediction

Themes: Machine Learning • Data Science • Artificial Intelligence

Mathematical Engineering of Deep Learning — Benoit Liquet

Mathematical Engineering of Deep Learning

Themes: Machine Learning • Data Science • Artificial Intelligence

Healthcare Solutions Using Machine Learning and Informatics — Punit Gupta

Healthcare Solutions Using Machine Learning and Informatics

Themes: Machine Learning • Data Science • Artificial Intelligence

Machine Learning with OneAPI — Shriram K. Vasudevan

Machine Learning with OneAPI

Shriram K. Vasudevan

Themes: Machine Learning • Data Science • Artificial Intelligence

Machine Learning For Physicists A Hands-on Approach — Sadegh Raeisi

Machine Learning For Physicists A Hands-on Approach

Themes: Machine Learning • Data Science • Artificial Intelligence

Applied Machine Learning Using Mlr3 in R — Bernd Bischl

Applied Machine Learning Using Mlr3 in R

Themes: Machine Learning • Data Science • Artificial Intelligence

A curated shelf of 24 read-alikes for Probabilistic Machine Learning An Introduction by Kevin P. Murphy — spanning Machine Learning, Data Science, Artificial Intelligence and featuring authors such as Ann Jackson, Chrystopher L. Nehaniv, Sandeep Reddy, Mark Chang, and others.

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