000			01584nam a22002777i 4500
005			20250722160934.0
008			250722s2021 ii ao||fr|||| 00| 0 eng d
020			_a9789389423617
040			_aEG-GaU‬‬ _cEG-GaU‬‬ _dEG-GaU‬‬ _erda
082	0	4	_223 _a006.3 _bc.e.b.
100	1		_aChopra, Deepti, _eauthor. _960466
245	1	0	_aBuilding machine learning systems using Python : _bpractice to train predictive models and analyze machine learning results with real use‑cases / _cDr Deepti Chopra.
250			_a 1st edition.
264		1	_aNew Delhi : _bBPB Publications, _c2021.
300			_a136 pages ; _c24 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
504			_aIncludes bibliographical references.
505			_a1. Introduction to Machine Learning ‡ 2. Linear Regression ‡ 3. Classification Using Logistic Regression ‡ 4. Overfitting and Regularization ‡ 5. Feasibility of Learning ‡ 6. Support Vector Machine ‡ 7. Neural Network ‡ 8. Decision Trees ‡ 9. Unsupervised Learning ‡ 10. Theory of Generalization ‡ 11. Bias and Fairness in ML.
520			_aA beginner‑friendly guide to machine learning with practical implementations of regression, classification, clustering, SVM, decision trees, neural networks, and unsupervised learning using Python and scikit‑learn. :contentReference[oaicite:1]{index=1}
650		0	_aMachine learning.
650		0	_aPredictive analytics. _960467
942			_2ddc _cBK
999			_c11082 _d11082