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Before Machine Learning Volume 2 - Calculus for A.I
Before Machine Learning Volume 2 - Calculus for A.I

Before Machine Learning Volume 2 - Calculus for A.I: The Fundamental Mathematics for Data Science and Artificial Intelligence

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Profile Icon Jorge Brasil
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€7.99
eBook Nov 2024 314 pages 1st Edition
eBook
€7.99
Arrow left icon
Profile Icon Jorge Brasil
Arrow right icon
€7.99
eBook Nov 2024 314 pages 1st Edition
eBook
€7.99
eBook
€7.99

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Key benefits

  • A step-by-step guide to calculus concepts tailored for AI and machine learning applications
  • Clear explanations of advanced topics like Taylor Series, gradient descent, and backpropagation
  • Practical insights connecting calculus principles directly to neural networks and data science

Description

This book takes readers on a structured journey through calculus fundamentals essential for AI. Starting with “Why Calculus?” it introduces key concepts like functions, limits, and derivatives, providing a solid foundation for understanding machine learning. As readers progress, they will encounter practical applications such as Taylor Series for curve fitting, gradient descent for optimization, and L'Hôpital’s Rule for managing undefined expressions. Each chapter builds up from core calculus to multidimensional topics, making complex ideas accessible and applicable to AI. The final chapters guide readers through multivariable calculus, including advanced concepts like the gradient, Hessian, and backpropagation, crucial for neural networks. From optimizing models to understanding cost functions, this book equips readers with the calculus skills needed to confidently tackle AI challenges, offering insights that make complex calculus both manageable and deeply relevant to machine learning.

Who is this book for?

Aspiring AI engineers, machine learning students, and data scientists will find this book valuable for building a strong calculus foundation. A basic understanding of calculus is beneficial, but the book introduces essential concepts gradually for all levels.

What you will learn

  • Explore the essentials of calculus for machine learning
  • Calculate derivatives and apply them in optimization tasks
  • Analyze functions, limits, and continuity in data science
  • Apply Taylor Series for predictive curve modeling
  • Use gradient descent for effective cost-minimization
  • Implement multivariable calculus in neural networks

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Nov 22, 2024
Length: 314 pages
Edition : 1st
Language : English
ISBN-13 : 9781836200680
Category :
Languages :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon DRM FREE - Read whenever, wherever and however you want

Product Details

Publication date : Nov 22, 2024
Length: 314 pages
Edition : 1st
Language : English
ISBN-13 : 9781836200680
Category :
Languages :

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