Machine Learning
Stores where to buy this product
Sponsored This site contains affiliate links for which we may receive compensation. More information
This product has not been found in any sponsored store recently, please check similar products from our sponsors or review other stores we offer where you may find the product.
Similar products
| This product in Comparor | |
|---|---|
|
Category
This product is cataloged in our store in these categories
|
|
|
International
Find this product in one of our international stores
|
This product has not been found in other countries
|
| Colors
Predominant colors of the product |
|
| Identifiers | |
| ISBN | 0070428077 |
| MPN | 9780070428072 |
| ID | 13892525 |
| Dimensions / Weight | |
| Key Features | |
Related articles
(9780128042915) - Country of publication: UNITED STATES - Dimensions: (H) 234mm, (W) 190mm, (D) 28mm - Edition: 4 ed - Paperback: 654 pages - Publisher: Morgan Kaufmann; 4 edition (22 Dec. 2016) - Morgan Kaufmann Publishers In
(9780141979243) - Dimensions: 198 x 129 x 20 mm - Format: 352 pages - Height: 131 mm - Spine width: 24 mm - Width: 198 mm - Penguin Books - London, United Kingdom - Penguin Books Ltd - ISBN: 9780141979243 | Master Algorithm
(9780262035613 / 45189572) - Country of publication: UNITED STATES - Dimensions: 229 x 178 x 32 mm - Format: 800 pages - Height: 187 mm - Spine width: 35 mm - Width: 237 mm - The MIT Press - In Print | Deep Learning techniques
(9780387310732) - Dimensions: 178 x 254 x 43.18mm | 2,147g - Edition: 1st ed. 2006. Corr. 2nd printing 2011 - Format: 738 pages - ISBN: 9780387310732 - Number of pages: 738 - Languages: English - Publication place: New York, NY, United States
A comprehensive guide that blends statistical theory with practical algorithms, covering Bayesian inference, neural networks, and support vector machines to master pattern recognition and machine learning.
(9780262035613 / 45189572) - Country of publication: UNITED STATES - Dimensions: 229 x 178 x 32 mm - Format: 800 pages - Height: 187 mm - Spine width: 35 mm - Width: 237 mm - The MIT Press - In Print | Deep Learning techniques