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Calculus For Machine Learning: Foundations and Applications
Paperback
Publisher: Independently Published
Published: Feb 15 2025
Pages: 88
Weight: 0.28
Height: 0.18 Width: 6.00 Depth: 9.00
Language: English
Machine learning has transformed the way we approach data, enabling us to build models that can learn from and make predictions on complex datasets. At the heart of many ML algorithms lies calculus, the branch of mathematics that deals with rates of change and accumulation. From optimizing loss functions to training neural networks, calculus provides the tools necessary to understand and improve these models.
This book is structured to take you on a journey from the fundamental concepts of calculus to their advanced applications in ML. We begin with a review of essential calculus topics, ensuring that readers have a solid foundation. We then delve into more specialized areas, such as gradient descent, backpropagation, and optimization techniques, illustrating how these concepts are applied in real-world ML problems.
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