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Visual Maths for ML: Discrete Mathematics
Count. Connect. Search. Decide.
This book is 100% completeLast updated on 2026-10-18
Explore sets, logic, counting, graphs, search and planning through annotated diagrams and worked examples. Includes a 37-page PDF and fixed-layout EPUB.
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About
About the Book
Build intuition for discrete mathematics through annotated diagrams, worked examples and conversations with Aarav and Maya.
What you will learn
• Sets and logic: group objects and combine yes/no rules.
• Counting and probability: reason about choices and chance.
• Graphs, trees and traversal: represent connections and explore structures.
• Search and task order: find routes and organise dependencies.
• Learning on graphs: connect graph structure to machine learning.
• Planning and reinforcement learning: reason about actions and uncertain outcomes.
• Practice questions and worked answers.
Included: a 37-page PDF and fixed-layout EPUB, comprising a cover plus all 36 illustrated lesson and reference pages. The EPUB includes page navigation and preserves the diagrams. Text does not reflow; small screens may require zooming. Use an EPUB reader that supports fixed layouts.
Download the free sample to explore the complete learning map.
By Pramod Tyagi · www.bitmonkey.ai
© 2026 Bitmonkey IT Services Pvt Ltd. All rights reserved.
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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 Visual Maths for ML series uses annotated diagrams, worked examples and practical scenarios to help readers build intuition for the mathematics behind machine learning.
Explore his work at www.bitmonkey.ai.
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