000			01708nam a22003017i 4500
005			20250821113549.0
008			250805s2021 ii a|||fr|||| 001 0 eng d
020			_a9788194837756
040			_aEG-GaU‬‬ _cEG-GaU‬‬ _dEG-GaU‬‬ _erda
082	0	4	_223 _a006.3 _bG.I.N
100	1		_aGridin, Ivan, _eauthor. _960436
245	1	0	_aLearning Genetic Algorithms with Python : _bempower the performance of machine learning and AI models with the capabilities of a powerful search algorithm / _cIvan Gridin.
250			_aFirst edition.
264		1	_aNew Delhi : _bBPB Publications, _c2021.
300			_a253 pages : _billustrations ; _c24 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
504			_aIncludes index.
505			_a1. Introduction -- 2. Genetic Algorithm Flow -- 3. Selection -- 4. Crossover -- 5. Mutation -- 6. Effectiveness -- 7. Parameter Tuning -- 8. Black-box Function -- 9. Combinatorial Optimization: Binary Gene Encoding -- 10. Combinatorial Optimization: Ordered Gene Encoding -- 11. Other Common Problems -- 12. Adaptive Genetic Algorithm -- 13. Improving Performance.
520			_aA complete practical guide to implementing genetic algorithms in Python for optimization in machine learning and AI. Covers core principles such as selection, crossover, mutation, parameter tuning, and real-world applications with hands-on examples.
650		4	_aGenetic algorithms (Computer science) _963118
650		4	_aPython (Computer program language). _962354
650		4	_aMachine learning. _962367
650		4	_aArtificial intelligence.
942			_2ddc _cBK
999			_c12062 _d12062