A comprehensive guide covering core algorithm concepts, data structures, and analysis techniques, this edition offers clear explanations, practical examples, and rigorous proofs to deepen understanding of computational problem solving.
(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
(9780262018029) - Dimensions: 229 x 203 x 41 mm - Height: 241 mm - Spine width: 44 mm - Width: 213 mm - The MIT Press - ISBN: 9780262018029 - Number of pages: 1067 - Languages: English - Publication date: 18 Sep | Probabilistic Perspective Hardback
(9780262201629 / 21151602) - Country of publication: UNITED STATES - Dimensions: (H) 238mm, (W) 211mm, (D) 36mm - MIT Press - MIT Press Ltd - In Print - ISBN: 9780262201629 - Page count: 672
Explore Gaussian Processes for Machine Learning and master probabilistic modeling with intuitive explanations, practical examples, and advanced inference techniques that empower data scientists to build robust predictive models.
(9780262039246) - Dimensions: 178 x 229 x 38mm | 1,179.34g - Second edition - The MIT Press - xxii, 526 - Massachusetts, United States - Format: Hardback | 552 pages - Publication date: 13 Nov 2018 - Height: 236mm
(9780262013192 / 26369268) - Dimensions: 229 x 203 x 49 mm - Height: 230 mm - Spine width: 55 mm - Width: 208 mm - The MIT Press - ISBN: 9780262013192 - Number of pages: 1231 - Languages: English - Weight: 2180 g | Probabilistic models
MIT Press (9780262043533) | Achievement Relocked
MIT Press (9780262039512) | Neural nets, Natural-language processing, Deep reinforcement
