| 000 | 01682nam a22002777i 4500 | ||
|---|---|---|---|
| 005 | 20250819140058.0 | ||
| 008 | 250807s2020 ii a|||fr|||| 00| 0 eng d | ||
| 020 | _a9789389845426 | ||
| 040 |
_aEG-GaU _cEG-GaU _dEG-GaU _erda |
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| 082 | 0 | 4 |
_223 _a006.3 _bb.h.m. |
| 100 | 1 |
_aBhasin, Harsh, _eauthor. _960102 |
|
| 245 | 1 | 0 |
_aMachine Learning for Beginners: _bLearn to Build Machine Learning Systems Using Python / _cHarsh Bhasin. |
| 250 | _afirst edition. | ||
| 264 | 1 |
_aNew Delhi : _bBPB Publications, _c2020. |
|
| 300 |
_a244 pages : _billustrations ; _c23 cm. |
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| 336 |
_2rdacontent _atext _btxt |
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| 337 |
_2rdamedia _aunmediated _bn |
||
| 338 |
_2rdacarrier _avolume _bnc |
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| 504 | _aIncludes feature selection techniques, classification algorithms, neural networks, PCA and appendix cheat sheets. | ||
| 505 | _aIntroduction to ML; Pre‑processing & Feature Selection; Regression; Classification (K‑NN, Logistic Regression, Naïve Bayes, LDA); Neural Networks I & II; SVM and Kernel Methods; Decision Trees; Clustering; Feature Extraction; Appendix (Cheat Sheets, Face Detection). | ||
| 520 | _aA hands-on guide to essential machine learning workflows using Python. Covers preprocessing, feature extraction, key classification algorithms, neural networks, SVMs, and clustering with practical examples. Aimed at undergraduate and postgraduate students and professionals entering ML via real-world implementations.turn0search2turn0search9turn0search5 | ||
| 650 | 0 |
_aMachine learning _xintroductory. _961814 |
|
| 650 | 0 |
_aData science _xmachine learning. _961815 |
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| 942 |
_2ddc _cBK |
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| 999 |
_c11586 _d11586 |
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