| 000 | 00202 a2200085 4500 | ||
|---|---|---|---|
| 999 |
_c86732 _d86731 |
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| 005 | 20180202121643.0 | ||
| 008 | 180106b ||||| |||| 00| 0 eng d | ||
| 020 | _a9781119183600 | ||
| 100 | _aBowles Michael | ||
| 245 | _aMachine Learning in Python:for predictive analysis | ||
| 260 |
_bWiley _c2015 |
||
| 500 | _a The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. | ||
| 650 | _2 Machine learning | ||
| 653 | _aMachine Learning in Python | ||
| 653 | _aComputer program language | ||
| 856 | _uhttp://onlinelibrary.wiley.com/book/10.1002/9781119183600 | ||
| 942 | _cEB | ||