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135438898
World Standard MIT Textbook Strang: Linear Algebra and Data Science Tankobon Hardcover – October 28, 2021
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Item #:
135438898
SAR 274
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A linear algebra textbook essential to the information age that data scientists should know!
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What Stands Out
Comprehensive Coverage
This textbook offers an extensive exploration of linear algebra principles tailored for data science applications, ensuring readers gain a solid foundation and practical insights.
MIT Quality
Authored by renowned educator Gilbert Strang, this book reflects MIT's high academic standards, providing users with top-tier educational content recognized globally.
Hardcover Durability
The tankobon hardcover format ensures durability for frequent use, making it an ideal investment for students and professionals seeking a reliable reference for linear algebra in data science.
Product Details
| Publisher | u8fd1u4ee3u79d1u5b66u793e (October 28, 2021) |
| Publication date | October 28, 2021 |
| Language | Japanese |
| Tankobon Hardcover | 488 pages |
| ISBN-10 | 4764906007 |
| ISBN-13 | 978-4764906006 |
| Dimensions | 10.12 x 7.17 x 0.79 inches (25.7 x 18.2 x 2 cm) |
Who Should Buy?
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Students of Mathematics
Ideal for undergraduate or graduate students studying linear algebra and its applications in data science.
-
Data Science Professionals
Beneficial for practitioners seeking to deepen their understanding of linear algebra in data analysis and machine learning.
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Self-learners
Great for individuals looking to advance their knowledge independently in linear algebra and its relevance to data science.
-
Beginners in Math
Not suitable for those without a basic understanding of mathematical concepts, as it may be too advanced.
Product Description
World Standard MIT Textbook Strang: Linear Algebra and Data Science Tankobon Hardcover – October 28, 2021
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Features & Benefits
- Essential reading for aspiring data scientists.
- Covers fundamental mathematics including linear algebra, probability statistics, and optimization.
- Written by MIT Professor Gilbert Strang, a noted expert in the field.
- Deep understanding of linear algebra is crucial for grasping neural networks and deep learning.
- Advanced textbook suitable for students and professionals alike.
- Few resources cover the underlying mathematics of deep learning like this book.
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