Before Machine Learning - Volume 1: Linear Algebra -The Fundamental Mathematics for Data Science and Artificial Intelligence (Grayscale Indian Edition)
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Before Machine Learning - Volume 1: Linear Algebra -The Fundamental Mathematics for Data Science and Artificial Intelligence (Grayscale Indian Edition)

Before Machine Learning - Volume 1: Linear Algebra -The Fundamental Mathematics for Data Science and Artificial Intelligence (Grayscale Indian Edition)


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About the Book

Disclaimer Shroff Publishers do not endorse the preview pages of kindle linked to our ISBNs. All Indian Reprints of Jorge Brazil Titles are Printed in Grayscale. Why: Linear algebra is a fundamental topic for anyone working in machine learning, and it plays a critical role in understanding the inner workings of algorithms and data models. In this book, you’ll learn how to apply linear algebra to real-world problems and gain a deep understanding of the concepts that drive machine learning. What is different: What sets this book apart is its different approach to teaching. Rather than presenting abstract mathematical concepts in isolation, the content is structured like a story with real-life examples that illustrate the practical applications of linear algebra. It is written in a conversational style as if you were having a one-on-one conversation with me, and the structure resembles a story. To whom: Whether you’re a beginner or an experienced practitioner, this book will help you master the essentials of linear algebra and build a solid foundation for your machine-learning journey. It assumes no prior knowledge of linear algebra, making it perfect for beginners. However, it also includes advanced concepts, making it a valuable resource for more experienced learners. What's inside: This book covers all the essential topics in linear algebra, from vectors and matrices to eigenvalues and eigenvectors. It also includes in-depth discussions of applications of linear algebra, such as principal component analysis, and single-value decomposition. Vectors addition. Multiplication of a vector by a scalar. The dot product. Vectors spaces, linear combinations, linear independence, and basis. Change of basis.


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Product Details
  • ISBN-13: 9789355424402
  • Publisher: Shroff/Jorge Brazil
  • Binding: Paperback
  • Height: 8.89 mm
  • No of Pages: 164
  • Width: 250 mm
  • ISBN-10: 935542440X
  • Publisher Date: 28 Jul 2023
  • Edition: First Edition
  • Language: English
  • Weight: 152.4 gr


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Before Machine Learning - Volume 1: Linear Algebra -The Fundamental Mathematics for Data Science and Artificial Intelligence (Grayscale Indian Edition)
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Before Machine Learning - Volume 1: Linear Algebra -The Fundamental Mathematics for Data Science and Artificial Intelligence (Grayscale Indian Edition)
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