| 000 | 02698nam a2200289 a 4500 | ||
|---|---|---|---|
| 001 | 50859 | ||
| 003 | 0000000000 | ||
| 005 | 20240411193249.0 | ||
| 008 | 230303n s 000 0 eng d | ||
| 020 | _a9783319307176 | ||
| 100 | 1 | _aUnpingco, José. | |
| 245 | 1 | 0 |
_aPython for probability, statistics, and machine learning _h[electronic resource] / _cJosé Unpingco. |
| 260 |
_aSwitzerland : _bSpringer International Publishing, _c2016. |
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| 300 | _a1 online resource. | ||
| 505 | 0 | _aGetting Started with Scientific Python Probability Statistics Machine Learning Notation. | |
| 520 | _aThis book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming. Explains how to simulate, conceptualize, and visualize random statistical processes and apply machine learning methods; Connects to key open-source Python communities and corresponding modules focused on the latest developments in this area; Outlines probability, statistics, and machine learning concepts using an intuitive visual approach, backed up with corresponding visualization codes. | ||
| 650 | 7 |
_aCommunications engineering _xtelecommunications. _2sears |
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| 650 | 7 |
_aData mining. _2sears |
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| 650 | 7 |
_aMaths for computer scientists. _2sears |
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| 650 | 7 |
_aMaths for engineers. _2sears |
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| 650 | 7 |
_aProbabilities _xData processing. _2sears |
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| 650 | 7 |
_aProbability & statistics. _2sears |
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| 650 | 7 |
_aPython (Computer program language) _2sears |
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| 650 | 7 |
_aStatistics _xData processing. _2sears |
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| 856 | _uhttps://drive.google.com/file/d/1XUTT4lxR7N5cTXdk-hRh_w2v-5NjS1KW/view?usp=sharing | ||
| 999 |
_c16158 _d16158 |
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