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Tag: Inteligence
Before Machine Learning Volume 1 – Linear Algebra for A.I: The fundamental mathematics for Data Science and Artificial Inteligence.
Price: $29.99
(as of Dec 24,2024 04:31:30 UTC – Details)From the Publisher
Customer Reviews
Price
Subject
Linear Algebra
Calculus
Probability and StatisticsASIN : B0CW2HDQJ9
Publisher : Independently published (February 20, 2024)
Language : English
Paperback : 164 pages
ISBN-13 : 979-8880261352
Item Weight : 10.7 ounces
Dimensions : 6 x 0.37 x 9 inchesCustomers say
Customers find the book well-written and accessible. They appreciate its clear explanations and visuals that make difficult concepts easier to understand. The book starts from the basics and works at a reasonable pace to establish core machine learning principles. Many customers find it useful and consider it one of the best books in math or science. However, opinions differ on the humor – some find it amusing and engaging, while others find it distracting.
AI-generated from the text of customer reviews
Before diving into machine learning, it’s crucial to have a solid understanding of the foundational mathematics that underpin it. In this new series, we will be exploring the essential mathematical concepts that are essential for data science and artificial intelligence.Volume 1 of this series will focus on linear algebra, a branch of mathematics that deals with vectors, matrices, and linear transformations. Linear algebra plays a crucial role in machine learning, as it provides the mathematical framework for representing and manipulating data.
In this volume, we will cover topics such as vector spaces, linear transformations, matrix operations, eigenvalues, and eigenvectors. Understanding these concepts will not only help you better grasp the inner workings of machine learning algorithms but also enable you to effectively apply them in real-world scenarios.
Whether you’re a beginner looking to build a strong foundation in mathematics for data science and AI or a seasoned practitioner looking to brush up on your linear algebra skills, this series is for you. Stay tuned for more in-depth discussions and practical examples that will help you master the fundamentals of linear algebra for AI.
#Machine #Learning #Volume #Linear #Algebra #A.I #fundamental #mathematics #Data #Science #Artificial #InteligenceBefore Machine Learning Volume 1 – Linear Algebra for A.I: The fundamental mathematics for Data Science and Artificial Inteligence.
Price: $9.99
(as of Dec 17,2024 04:03:23 UTC – Details)From the Publisher
Customer Reviews
4.1 out of 5 stars
83
4.8 out of 5 stars
26
5.0 out of 5 stars
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Price
$9.99$9.99
$9.99$9.99
$9.99$9.99Subject
Linear Algebra
Calculus
Probability and StatisticsASIN : B0BZWN26WJ
Publication date : March 28, 2023
Language : English
File size : 4892 KB
Text-to-Speech : Not enabled
Enhanced typesetting : Not Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 161 pages
Format : Print Replica
Are you interested in diving into the world of machine learning but find yourself lost in the sea of complex mathematical concepts? Look no further than our new series, “Before Machine Learning Volume 1 – Linear Algebra for A.I.” In this book, we break down the fundamental mathematics that serve as the building blocks for data science and artificial intelligence.Linear algebra is the backbone of machine learning algorithms, providing the tools necessary to understand and manipulate data in a way that allows machines to learn and make predictions. From vectors and matrices to eigenvalues and eigenvectors, this book covers it all in a clear and concise manner that is accessible to readers of all levels of mathematical background.
Whether you are a beginner looking to get started in the field of data science or an experienced practitioner looking to brush up on your mathematical skills, “Before Machine Learning Volume 1 – Linear Algebra for A.I.” is the perfect resource for anyone looking to understand the essential mathematics behind machine learning. Stay tuned for more volumes in this series as we continue to explore the mathematical foundations of artificial intelligence.
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