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Visual Maths for ML: Bayesian Inference
Update beliefs with evidence.
This book is 100% completeLast updated on 2026-10-19
Update beliefs with evidence. Explore bayesian inference through annotated diagrams and worked examples. Includes PDF and EPUB.
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About
About the Book
Build intuition with annotated diagrams, worked examples and practical explanations.
What you will learn
Priors, likelihoods and posteriors; predictions and uncertainty; simple and richer Bayesian models.
Includes a 38-page PDF and fixed-layout EPUB: a cover plus all 37 corrected illustrated lesson pages. The EPUB preserves the diagrams and includes page navigation. Text does not reflow; small screens may require zooming.
Download the free opening lesson to explore the book before buying.
By Pramod Tyagi · www.bitmonkey.ai
© 2026 Bitmonkey IT Services Pvt Ltd. All rights reserved.
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Author
About the Author
Pramod Tyagi
Pramod Kumar Tyagi is an AI and digital architect with more than 20 years of experience designing and scaling enterprise technology platforms. He is the founder of Bitmonkey IT Services Pvt Ltd, where his work spans AI products, digital transformation and interactive AI/ML education.
Previously, Pramod served as Principal Architect and Head of Enterprise Integration & AI Centre of Excellence at NTT DATA Services. His experience includes AI and machine learning, cloud architecture, data platforms and intelligent automation across banking, payments, healthcare, retail and supply chain.
He holds an MS in Aerospace Engineering from the Indian Institute of Science (IISc), Bangalore, and is a TOGAF-certified solution architect.
His illustrated books use annotated diagrams, worked examples and practical scenarios to help readers build intuition for programming and the mathematics behind machine learning.
Explore his work at www.bitmonkey.ai.
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