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Essential Math for AI: Exploring Linear Algebra, Probability and Statistics, Calculus, Graph Theory, Discrete Mathematics, Numerical Methods, Optimiza

AUTHOR Hinton, Andrew
PUBLISHER Book Bound Studios (11/13/2023)
PRODUCT TYPE Paperback (Paperback)

Description

Are you ready to unlock the mathematical secrets that power today's most advanced artificial intelligence systems? "Essential Math for AI" is an essential guide for anyone looking to understand the complex mathematical underpinnings of AI. Whether you're an AI enthusiast, a student, or a professional in the field, this book is tailored to enrich your knowledge and prepare you for the future of AI innovation.


Here's what you'll discover inside:

  • Linear Algebra: Dive into the core of machine learning with in-depth explorations of vectors, matrices, and data transformations.
  • Probability and Statistics: Learn how to make sense of data and uncertainty, which is crucial for developing robust AI applications.
  • Calculus: Optimize AI models using the power of derivatives, integrals, and multivariable optimization.
  • Graph Theory: Model complex relationships and understand the algorithms that can navigate these structures in AI.
  • Discrete Mathematics: Tackle combinatorial problems and optimize algorithmic efficiency, a cornerstone of AI development.
  • Numerical Methods: Solve equations and approximate functions, enhancing the computational power of AI.
  • Optimization Techniques: From gradient descent to swarm intelligence, master the methods that enhance AI performance.
  • Game Theory: Analyze strategic decision-making and its profound implications in AI.
  • Information Theory: Quantify and encode data, ensuring efficiency and integrity in AI systems.
  • Topology and Geometry: Uncover hidden structures in data, paving the way for breakthroughs in AI research.


"Essential Math for AI" provides a comprehensive overview of the mathematical concepts propelling AI forward and offers a glimpse into the future of how these disciplines will continue to shape the AI landscape. With chapter summaries to consolidate your learning and a clear path charted for future exploration, this book is your roadmap to becoming well-versed in the mathematics of AI.


Take the next step in your AI journey. Embrace the mathematical challenges and opportunities with "Essential Math for AI."?

Show More
Product Format
Product Details
ISBN-13: 9781923045866
ISBN-10: 1923045865
Binding: Paperback or Softback (Trade Paperback (Us))
Content Language: English
More Product Details
Page Count: 158
Carton Quantity: 50
Product Dimensions: 6.00 x 0.34 x 9.00 inches
Weight: 0.48 pound(s)
Country of Origin: US
Subject Information
BISAC Categories
Mathematics | Probability & Statistics - Bayesian Analysis
Mathematics | Artificial Intelligence - Natural Language Processing
Mathematics | Geometry - Algebraic
Descriptions, Reviews, Etc.
publisher marketing

Are you ready to unlock the mathematical secrets that power today's most advanced artificial intelligence systems? "Essential Math for AI" is an essential guide for anyone looking to understand the complex mathematical underpinnings of AI. Whether you're an AI enthusiast, a student, or a professional in the field, this book is tailored to enrich your knowledge and prepare you for the future of AI innovation.


Here's what you'll discover inside:

  • Linear Algebra: Dive into the core of machine learning with in-depth explorations of vectors, matrices, and data transformations.
  • Probability and Statistics: Learn how to make sense of data and uncertainty, which is crucial for developing robust AI applications.
  • Calculus: Optimize AI models using the power of derivatives, integrals, and multivariable optimization.
  • Graph Theory: Model complex relationships and understand the algorithms that can navigate these structures in AI.
  • Discrete Mathematics: Tackle combinatorial problems and optimize algorithmic efficiency, a cornerstone of AI development.
  • Numerical Methods: Solve equations and approximate functions, enhancing the computational power of AI.
  • Optimization Techniques: From gradient descent to swarm intelligence, master the methods that enhance AI performance.
  • Game Theory: Analyze strategic decision-making and its profound implications in AI.
  • Information Theory: Quantify and encode data, ensuring efficiency and integrity in AI systems.
  • Topology and Geometry: Uncover hidden structures in data, paving the way for breakthroughs in AI research.


"Essential Math for AI" provides a comprehensive overview of the mathematical concepts propelling AI forward and offers a glimpse into the future of how these disciplines will continue to shape the AI landscape. With chapter summaries to consolidate your learning and a clear path charted for future exploration, this book is your roadmap to becoming well-versed in the mathematics of AI.


Take the next step in your AI journey. Embrace the mathematical challenges and opportunities with "Essential Math for AI."?

Show More

Author: Hinton, Andrew
Andrew Hinton is an Information Architect at The Understanding Group (TUG). Since the early 90s, he's been helping clients and employers of all shapes and sizes make better information environments. Andrew is co-founder and past board member of the IA Institute, and is a frequent speaker at UX conferences. You can find links to Andrew-related things at andrewhinton.com. Learn more about his book, Understanding Context, at contextbook.com
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Paperback