Computer science books
Suggestions for Computer science books
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(9781617293818 / 29283778) - Dimensions: 20 x 80 x 1mm | 588g - Format: 320 pages - ISBN: 9781617293818 - Languages: English - New York, United States - Manning Publications | Functional Programming in C++ & Functional Programming
(9781491973790 / 28258537) - Imprint: O'Reilly Media, Inc, USA
(9780141982410) - Judea Pearl - Penguin Books - x, 418 - London, United Kingdom - Penguin Books Ltd - Dimensions: 129 x 198 x 24mm | 315g - Format: Paperback | 432 pages - Height: 129mm - Spine width: 26mm | Artificial Intelligence
(9781107172418)
(9781119482086) - Marcos Lopez de Prado - Hardback, - John Wiley & Sons Inc - Pages: 400 - Publication date: 7 Feb 2018 - Weight: 662g
(9781119433385 / 50024353) - Dimensions: 153 x 228 x 16mm | 344g - Edition: 2nd Edition - Format: Paperback | 320 pages - Publication date: 07 Aug 2018 - ISBN: 9781119433385 - Number of pages: 320 - Languages: English | Book shows
(9780231159111)
(9781633696846 / 33316200) - Height: 209mm - Spine width: 17mm - Width: 140mm - Harvard Business Review Press - cm - ISBN: 9781633696846 - Languages: English - Publication date: 15 Jan 2019 - Weight: 220g
(9781260142679)
(9780071798686 / 37040319)
(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
Syngress Media,U.S. (9781597494861)
(9780393608885 / 50989526) - Dimensions: 165 x 244 x 30mm | 560g - First edition - W.W. Norton and Company - viii, 319 - New York, United States - W. W. Norton & Company - Format: Hardback | 288 pages | Kill Everybody
(9781498723633)
(9780198803201 / YES35862427)
(9781492039594) - Dimensions: 187 x 232 x 15.24mm | 476.27g - First edition - O'Reilly - Sebastopol, United States - O'Reilly Media - Format: 240 pages - Height: 231 mm - Spine width: 14 mm - Width: 186 mm
Addison-Wesley Educational Publishers Inc (9780133903355 / 23374977)
Cambridge University Press (9781316626221 / 45666918)
(9780198794141) - Fifth edition - Oxford University Press - xx, 408 - OUP Oxford - Height: 198 mm - Spine width: 19 mm - Width: 266 mm - ISBN: 9780198794141 - Languages: English - Weight: 940 g
(9781593277253) - Ages: 9-12 - Dimensions: 178 x 234 x 22.86mm | 680.39g - Format: 328 pages - ISBN: 9781593277253 - Languages: English - San Francisco, United States - No Starch Press,US | Willbee the Bumblebee
Atlantic Books (9781782394853 / MAN-MRD-U292-1782394850)
Barnett James (9781430264668 / 188 black & white illustrations, biograp)
(9781484230299 / 48705462)
John Wiley & Sons Inc (9781118551479 / YES8073165)
O'Reilly Media, Inc, USA (9781491938614)
Ingramcontent (9781119386339 / 26480059)
(9781119448327) - Dimensions: 196 x 228 x 16mm | 696g - Format: Paperback | 352 pages - Publication date: 23 Oct 2017 - ISBN: 9781119448327 - Languages: English - New York, United States - John Wiley & Sons Inc
Pearson Education Limited (9781292140414) - Available - E-commerce: business aspects - Mixed media product - Pearson Education Limited - Dimensions: 276 x 221 x 23 mm - ISBN: 9781292140414 - Publication date: 26/07/2016
No Starch Press,US (9781593276898 / illustrations)
(9781840788327) - Dimensions: 227 x 186 mm - Edition: 2nd 2018 edition - Height: 185 mm - Spine width: 12 mm - Width: 225 mm - In Easy Steps - In Easy Steps Limited - ISBN: 9781840788327 - Number of pages: 240 | Photoshop CC
(9781784780456 / 30041570) - Height: 137 mm - Spine width: 29 mm - Width: 230 mm - Verso - Verso Books - ISBN: 9781784780456 - Number of pages: 34 - Languages: English - Weight: 394 g
(9780134686479 / 48318935)
(9780321205681 / 978-0-3212-0568-1) - Height: 233 mm - Spine width: 14 mm - Width: 178 mm - Addison-Wesley - Pearson Education - ISBN: 9780321205681 - Number of pages: 268 - Languages: English - Weight: 508 g
(9780134464541 / 9780134464541)
(9781617290893)
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.