#5576

Mentioned in 5 episodes

Pattern Recognition and Machine Learning

Book • 2006

Christopher M. Bishop

This book offers a detailed introduction to pattern recognition and machine learning, integrating both fields under a common statistical framework.

It covers topics such as Bayesian methods, graphical models, kernel-based algorithms, and neural networks, making it suitable for advanced undergraduates, first-year PhD students, researchers, and practitioners.

The book includes a wide range of exercises and is supported by additional materials like lecture slides and figures.

Mentioned by

Andrew Lawrence

Mentioned in 5 episodes

Mentioned by

Minqi Jiang

as a resource for self-study in machine learning.

#114 - Secrets of Deep Reinforcement Learning (Minqi Jiang)

Mentioned by

Bert de Vries

as a book that taught him machine learning basics.

Prof. BERT DE VRIES - ON ACTIVE INFERENCE

Mentioned by

Yannic Kilcher

when discussing the PRML book and model-based machine learning.

ICLR 2020: Yann LeCun and Energy-Based Models

Authored by

Chris Bishop

, serving as an essential reference for machine learning students and researchers.

Prof. Chris Bishop's NEW Deep Learning Textbook!

Mentioned by

Andrew Lawrence

as a good fundamental book for machine learning.

Causal AI, Modularity & Learning || Andrew Lawrence || Causal Bandits Ep. 002 (2023)

Mentioned by

Tim Scarfe

when preparing for the episode, referencing his forgotten knowledge of kernels.

Mentioned by

Sayak Paul

as a book recommended during his undergraduate course on Pattern Recognition and Machine Learning.

Mentioned by

Daniel Wilson

as a resource for learning machine learning.

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