Items related to Linear Algebra: Theory, Intuition, Code
Synopsis
Are you ready to dive into the vibrant world of linear algebra and learn how it powers real-world applications? Welcome to this comprehensive textbook, where traditional theory meets modern computational practices.
Linear algebra is the magic behind many computational sciences -- machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analyses, matrix decompositions, signal processing, and more. But here's a secret: the way it's taught in traditional textbooks isn't how professionals use it in the field.
For instance, have you ever wondered about the practical importance of a matrix's "determinant"? You might be in for a surprise! This book bridges the gap between theoretical understanding and practical application, showing you not only the “what” but also the “how” of implementing linear algebra in real-world scenarios.
What makes this book a must-have resource?
- Crystal-clear explanations of linear algebra concepts and theories.
- Multiple angles to explain ideas, a proven technique to help cement your understanding.
- Vivid graphical visualizations to enhance your geometric intuition of linear algebra.
- Real-world implementations in MATLAB and Python. After all, in today's world, you seldom solve math problems by hand. Software is the way forward!
- A range of topics from beginner to intermediate levels, including vectors, matrix multiplications, least-squares projections, eigendecomposition, and singular-value decomposition.
- Emphasis on the application-oriented aspects of linear algebra and matrix analysis.
- Intuitive visual explanations of diagonalization, eigenvalues and eigenvectors, and singular value decomposition.
- Ready-to-use codes in MATLAB and Python to bring linear algebra concepts to life on your computer. All codes can be downloaded from https://github.com/mikexcohen/LinAlgBook.
- A unique blend of hand-solved exercises and advanced code challenges. Remember, math is not a spectator sport!
Whether you're just starting your journey in linear algebra or seeking to apply these concepts to data analyses on computers (such as data science, machine-learning, or signal processing), this book is your go-to guide. With this book at your side, you won't just learn linear algebra; you'll experience it!
"synopsis" may belong to another edition of this title.
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Linear Algebra: Theory, Intuition, Code
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.
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Paperback. Condition: Very Good. Linear algebra is perhaps the most important branch of mathematics for computational sciences, including machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analyses, matrix decompositions, signal processing, and so on.The way linear algebra is presented in traditional textbooks is different from how professionals use linear algebra in computers to solve real-world applications in machine learning, data science, statistics, and signal processing. For example, the determinant of a matrix is important for linear algebra theory, but should you actually use the determinant in practical applications? The answer may surprise you If you are interested in learning the mathematical concepts linear algebra and matrix analysis, but also want to apply those concepts to data analyses on computers (e.g., statistics or signal processing), then this book is for you. You'll see all the math concepts implemented in MATLAB and in Python.Unique aspects of this book: - Clear and comprehensible explanations of concepts and theories in linear algebra. - Several distinct explanations of the same ideas, which is a proven technique for learning. - Visualization using graphs, which strengthens the geometric intuition of linear algebra. - Implementations in MATLAB and Python. Com'on, in the real world, you never solve math problems by hand You need to know how to implement math in software - Beginner to intermediate topics, including vectors, matrix multiplications, least-squares projections, eigendecomposition, and singular-value decomposition. - Strong focus on modern applications-oriented aspects of linear algebra and matrix analysis. - Intuitive visual explanations of diagonalization, eigenvalues and eigenvectors, and singular value decomposition. - Codes (MATLAB and Python) are provided to help you understand and apply linear algebra concepts on computers. - A combination of hand-solved exercises and more advanced code challenges. Math is not a spectator sport. Seller Inventory # 00103395242
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Linear Algebra: Theory, Intuition, Code
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Linear Algebra: Theory, Intuition, Code
Seller: World of Books Inc, Montgomery, IL, U.S.A.
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Paperback. Condition: Very Good. Linear algebra is perhaps the most important branch of mathematics for computational sciences, including machine learning, AI, data science, statistics, simulations, computer graphics, multivariate analyses, matrix decompositions, signal processing, and so on.The way linear algebra is presented in traditional textbooks is different from how professionals use linear algebra in computers to solve real-world applications in machine learning, data science, statistics, and signal processing. For example, the determinant of a matrix is important for linear algebra theory, but should you actually use the determinant in practical applications? The answer may surprise you If you are interested in learning the mathematical concepts linear algebra and matrix analysis, but also want to apply those concepts to data analyses on computers (e.g., statistics or signal processing), then this book is for you. You'll see all the math concepts implemented in MATLAB and in Python.Unique aspects of this book: - Clear and comprehensible explanations of concepts and theories in linear algebra. - Several distinct explanations of the same ideas, which is a proven technique for learning. - Visualization using graphs, which strengthens the geometric intuition of linear algebra. - Implementations in MATLAB and Python. Com'on, in the real world, you never solve math problems by hand You need to know how to implement math in software - Beginner to intermediate topics, including vectors, matrix multiplications, least-squares projections, eigendecomposition, and singular-value decomposition. - Strong focus on modern applications-oriented aspects of linear algebra and matrix analysis. - Intuitive visual explanations of diagonalization, eigenvalues and eigenvectors, and singular value decomposition. - Codes (MATLAB and Python) are provided to help you understand and apply linear algebra concepts on computers. - A combination of hand-solved exercises and more advanced code challenges. Math is not a spectator sport. Seller Inventory # CIN9083136604VG
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Linear Algebra: Theory, Intuition, Code
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ISBN 10: 9083136604
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