World Standard MIT Textbook Strang: Linear Algebra and Data Science Tankobon Hardcover – October 28, 2021
UZS 937300
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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
Mahsulot tafsilotlari
| 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.
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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.
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Beginners in Math
Not suitable for those without a basic understanding of mathematical concepts, as it may be too advanced.
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Casual Readers
Individuals looking for light reading will find the textbook's technical nature unengaging and challenging.
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Professionals Outside Discipline
Those working in fields unrelated to data science or mathematics may not benefit from the specialized content.
MAHSULOT TAVSIFI
World Standard MIT Textbook Strang: Linear Algebra and Data Science Tankobon Hardcover – October 28, 2021
Mijozlarning savol-javoblari
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Savol:
Is this book suitable for beginners in data science?
Javob: This book is designed as an advanced textbook, ideal for those with a foundational understanding of linear algebra. -
Savol:
What mathematical concepts does this book cover?
Javob: It covers linear algebra, probability statistics, and optimization, key components for data science. -
Savol:
Why is understanding linear algebra important for data scientists?
Javob: Linear algebra provides the mathematical foundation necessary for understanding neural networks and deep learning.
ギルバート・ストラング Editorial Review
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Pros
- Engaging and informative content
- Well-structured lessons
- Great for beginners
- Hands-on exercises included
- Expert insights provided
Kamchiliklari
- Some concepts may be slightly complex.
Product Price History
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UZS 937300
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Xususiyatlar va Afzalliklar
- 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.
