| 000 | 01695nam a22003137i 4500 | ||
|---|---|---|---|
| 005 | 20250807153122.0 | ||
| 008 | 250807s2021 ii a|||fr|||| 00| 0 eng d | ||
| 020 | _a9789391392352 | ||
| 040 |
_aEG-GaU _cEG-GaU _dEG-GaU _erda |
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| 082 | 0 | 4 |
_223 _a006.3 _bd.r.m. |
| 100 | 1 |
_aDoshi, Ruchi, _eauthor. _961789 |
|
| 245 | 1 | 0 |
_aMachine Learning : _bMaster Supervised and Unsupervised Learning Algorithms with Real Examples / _cRuchi Doshi, Kamal Kant Hiran, Ritesh Kumar Jain & Kamlesh Lakhwani. |
| 250 | _afirst edition. | ||
| 264 |
_aNew Delhi : _bBPB Publications, _c2021. |
||
| 300 |
_a294 pages : _billustrations ; _c23 cm. |
||
| 336 |
_2rdacontent _atext _btxt |
||
| 337 |
_2rdamedia _aunmediated _bn |
||
| 338 |
_2rdacarrier _avolume _bnc |
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| 504 | _aIncludes exercises and model question papers. | ||
| 505 | _aIntroduction; Supervised Learning; Unsupervised Learning; Statistical Learning Theory; Semi‑supervised & Reinforcement Learning; Recommender Systems. | ||
| 520 | _a=520 ## $aA clear, example-driven introduction to machine learning, covering key supervised, unsupervised, semi‑supervised, and reinforcement learning algorithms. Packed with Python code, real‑scenario cases, exercises, and model question papers—ideal for data science students and practitioners.turn0search5turn0search1turn0search3 | ||
| 650 | 0 |
_aMachine learning _xmethods. _961784 |
|
| 650 | 0 |
_aArtificial intelligence _xalgorithms. _961790 |
|
| 700 | 1 |
_aHiran, Kamal Kant, _eauthor. _961791 |
|
| 700 | 1 |
_aLakhwani, Kamlesh, _eauthor. _961792 |
|
| 700 | 1 |
_aJain, Ritesh Kumar, _eauthor. _961793 |
|
| 942 |
_2ddc _cBK |
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| 999 |
_c11580 _d11580 |
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