Mathematics for Machine Learning, (Hardcover)
MYR 576
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This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites.
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What Stands Out
Maklumat produk
| Book format | Hardcover |
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | April, 2020 |
| Pages | 390 |
| Reading level | General |
| Subgenre | Artificial Intelligence |
| Series title | No Series |
| Edition | 1 |
| Publisher | Cambridge University Press |
| Original languages | English |
| Language | English |
| Edu focus | Math & Counting |
| Educational level | College |
| Is collectible | N |
| Binding type | Case Binding |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 6.40 x 0.80 x 8.90 in (16.3 x 2 x 22.6 cm) |
| Assembled product weight | 2.1 lb (950 grams) |
| Bisac subject heading | Computers |
PENERANGAN PRODUK
Mathematics for Machine Learning, (Hardcover)
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Marc Peter Deisenroth All Books Editorial Review
Mathematics for Machine Learning is a hardcover non-fiction book published by Cambridge University Press in April 2020. Spanning 390 pages, it covers essential mathematical concepts necessary for understanding machine learning, making it ideal for college-level readers. This book is categorized within the Computing & Internet genre and specifically addresses topics in Artificial Intelligence, which is crucial for anyone looking to dive deeper into the field of machine learning. Its informative content has been positively received by readers seeking to strengthen their math foundation for advanced computing studies.
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Ulas Produk Ini
Kongsikan pandangan anda dengan pelanggan lain
Kebaikan
- Comprehensive coverage of necessary mathematical concepts
- Designed for college-level understanding
- High-quality hardcover format
- Focuses on Artificial Intelligence applications
- Useful for both beginners and advanced learners
Keburukan
- Some readers may find it dense in parts
Product Price History
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MYR 576
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Ciri & Faedah
- Comprehensive introduction to essential mathematical tools for machine learning.
- Covers linear algebra, probability, statistics, and more in a unified approach.
- Bridges the gap between disparate courses for efficient learning.
- Includes derivations of key machine learning methods for practical application.
- Every chapter offers worked examples and exercises to enhance understanding.
- Accompanying programming tutorials available on the book's website.
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