000 | 01651cam a2200301 i 4500 | ||
---|---|---|---|
001 | 22069826 | ||
005 | 20230815143204.0 | ||
008 | 210607s2022 mau b 001 0 eng | ||
020 |
_a9780262046824 _q(hardcover) |
||
040 |
_aDLC _beng _cEC-QuPUC _erda _dEC-QuPUC |
||
041 | _aenm | ||
042 | _apcc | ||
082 | 0 | 0 |
_a006.31 _bM954p _223 |
100 |
_aMurphy, Kevin P., _977254 _eorg |
||
245 | 1 | 0 |
_aProbabilistic machine learning : _ban introduction / _cKevin P. Murphy. |
264 | 1 |
_aCambridge, Massachusetts : _bThe MIT Press, _c2022 |
|
300 |
_axxix, 826 pages : _billustrations (some color) ; _c24 cm |
||
336 | _atxt | ||
337 | _an | ||
338 | _anc | ||
490 | 0 |
_aAdaptive computation and machine learning series _977255 |
|
504 | _aIncludes bibliographical references and index. | ||
520 | _a"This book provides a detailed and up-to-date coverage of machine learning. It is unique in that it unifies approaches based on deep learning with approaches based on probabilistic modeling and inference. It provides mathematical background (e.g. linear algebra, optimization), basic topics (e.g., linear and logistic regression, deep neural networks), as well as more advanced topics (e.g., Gaussian processes). It provides a perfect introduction for people who want to understand cutting edge work in top machine learning conferences such as NeurIPS, ICML and ICLR"-- | ||
650 | 7 |
_aAprendizaje automático (Inteligencia artificial) _2 _945327 |
|
650 | 7 |
_aProbabilidades _962163 |
|
856 | _uhttps://puce.odilo.us/info/probabilistic-machine-learning-an-introduction-03131947 | ||
942 |
_cBK _00 |
||
999 |
_c283425 _d283425 |