000			01888nam a22002777i 4500
005			20250915105459.0
008			250723s2022 ii ao||fr|||| 00| 0 eng d
020			_a9789389328622
040			_aEG-GaU‬‬ _cEG-GaU‬‬ _dEG-GaU‬‬ _erda
082	0	4	_223 _a658.404 _bS.S.M
100	1		_aSingla, Saurav, _eaurhor _960498
245	1		_aMachine learning for finance : _bbeginner’s guide to explore machine learning in banking and finance / _cSaurav Singla.
250			_a 1st edition.
264		1	_aNew Delhi : _bBPB Publications, _c2020.
300			_a240 pages : _billustrations ; _c24 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
504			_aIncludes bibliographical references.
505	0		_a1. Introduction ‡ 2. Naïve Bayes, Normal Distribution & Clustering ‡ 3. Machine Learning for Data Structuring ‡ 4. Parsing Data Using NLP ‡ 5. Computer Vision ‡ 6. Neural Networks, GBM & Gradient Descent ‡ 7. Sequence Modeling ‡ 8. Reinforcement Learning for Financial Markets ‡ 9. Finance Use Cases ‡ 10. Impact of Machine Learning on Fintech ‡ 11. Machine Learning in Finance ‡ 12. e‑KYC & Anti‑Fraud Policy ‡ 13. Data Mining & Visualization ‡ 14. Advantages & Disadvantages of ML ‡ 15. Applications in Other Industries ‡ 16. Ethical Considerations in AI ‡ 17. AI in Banking ‡ 18. Common ML Algorithms ‡ 19. Frequently Asked Questions.
520			_aA practical introduction to machine learning applications in the financial sector, covering algorithms, NLP, computer vision, reinforcement learning, ethics, and real-world finance use cases.([turn0search2])([turn0search8])
650		0	_aMachine learning _xApplications. _960499
650		0	_aFinancial services _xData processing. _960500
942			_2ddc _cBK
999			_c11095 _d11095