World Standard MIT Textbook Strang: Liberal Arts Linear Algebra Tankobon Hardcover – March 14, 2023
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Learn world-standard linear algebra as an education!
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Информация за продукта
| Publisher | u8fd1u4ee3u79d1u5b66u793e |
| Publication date | March 14, 2023 |
| Language | Japanese |
| Print length | 433 pages |
| ISBN-10 | 4764906457 |
| ISBN-13 | 978-4764906457 |
| Item Weight | 780 g |
| Dimensions | 7.17 x 0.79 x 10.12 inches (18.2 x 2 x 25.7 cm) |
Who Should Buy?
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University Students
Ideal for undergraduates pursuing mathematics or related fields, providing foundational knowledge in linear algebra concepts.
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Self-Learners
Perfect for individuals learning independently, offering clear explanations and extensive practice problems for mastery.
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Educators
A valuable resource for teachers and professors seeking a thorough textbook to support instruction in linear algebra.
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Beginners
Not suitable for absolute novices; requires basic understanding of algebra and mathematical concepts for effective comprehension.
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Casual Readers
May not engage those looking for light reading; it’s structured as an academic textbook with dense content.
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Budget-Conscious
Higher priced hardcover edition might not appeal to those needing affordable learning materials without compromising on quality.
ОПИСАНИЕ НА ПРОДУКТА
World Standard MIT Textbook Strang: Liberal Arts Linear Algebra Tankobon Hardcover – March 14, 2023
Въпроси на клиенти и отговори
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въпрос:
Who is the author of the book?
отговор: The book is authored by Dr. Strang, a famous professor at MIT. -
въпрос:
What is the main focus of this textbook?
отговор: The textbook focuses on teaching the concept of linear algebra, particularly vector spaces and their applications. -
въпрос:
Is this book suitable for beginners?
отговор: Yes, it's suitable for everyone from students to researchers, including beginners in linear algebra.
Gilbert Strang (Original Author) Editorial Review
**** The "世界標準MIT教科書 ストラング:教養の線形代数" offers a refreshing and engaging approach to learning linear algebra, particularly appealing to those who have previously struggled with traditional textbooks. The narrative style mirrors that of a lecture, making complex concepts more accessible and enjoyable for students. Many reviewers noted that Strang's text has the unique ability to transform their perception of linear algebra from daunting to fun, thanks to its rich inclusion of practical applications, especially in areas such as statistics and machine learning. Illustrations, ample examples, and thoughtfully curated exercises contribute to a deeper understanding of the subject matter, helping students bridge the gap between theoretical concepts and their practical uses. While the book effectively maintains motivation through its relevancy to contemporary fields, some users did express concerns about the high price point relative to its length, suggesting that a more budget-friendly option would enhance its appeal significantly. Despite minor criticisms regarding undefined terms introduced early in the text—which may challenge absolute beginners—the Consensus highlights that those with some prior exposure to linear algebra will find this book an excellent resource for both review and new learning. With the additional support available online for exercise solutions, readers appreciate the depth this textbook provides in developing an intuitive grasp of linear algebra. **
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Професионалисти
- Engaging lecture-style narrative makes it enjoyable to read.
- Strong focus on practical applications, particularly in machine learning and data science.
- Rich illustrations and well-structured exercises enhance understanding.
- Encourages intuitive understanding of linear algebra concepts.
- Online resources available for practice problem solutions.
минуси
- High price relative to its length (400 pages).
Product Price History
Важна информация
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Характеристики и предимства
- Authored by renowned MIT professor Dr. Strang.
- Compact format makes learning linear algebra accessible.
- Focuses on vector spaces to enhance understanding.
- Includes applications relevant to data science.
- Rich in examples and practice questions for skill assessment.
- Suitable for students and researchers alike.
