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

Język publikacji: angielskim
Autor:
Jorge Brasil
Before Machine Learning Volume 2 - Calculus for A.I.  The Fundamental Mathematics for Data Science and Artificial Intelligence Jorge Brasil - okladka książki

Before Machine Learning Volume 2 - Calculus for A.I.  The Fundamental Mathematics for Data Science and Artificial Intelligence Jorge Brasil - okladka książki

Serie wydawnicze:
Essentials
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
314
Dostępny format:
     PDF

Ebook

39,90 zł

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Do przechowalni

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.

O autorze książki

Jorge Brasil is a mathematician with over a decade of experience in developing and deploying machine learning systems. His books are expertly written in a conversational style with a touch of humor. They are rich in practical applications, enabling readers to not only grasp the concepts but also understand their real-world applications in the field of Data Science.

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