| 000 | 01749cam a2200277zu 4500 | ||
|---|---|---|---|
| 001 | 88853126 | ||
| 003 | FRCYB88853126 | ||
| 005 | 20250107225204.0 | ||
| 006 | m o d | ||
| 007 | cr un | ||
| 008 | 250107s2015 fr | o|||||0|0|||eng d | ||
| 020 | _a9781784396053 | ||
| 035 | _aFRCYB88853126 | ||
| 040 |
_aFR-PaCSA _ben _c _erda |
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| 100 | 1 | _aLayton, Robert | |
| 245 | 0 | 1 |
_aLearning Data Mining with Python _c['Layton, Robert'] |
| 264 | 1 |
_bPackt Publishing _c2015 |
|
| 300 | _a p. | ||
| 336 |
_btxt _2rdacontent |
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| 337 |
_bc _2rdamdedia |
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| 338 |
_bc _2rdacarrier |
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| 650 | 0 | _a | |
| 700 | 0 | _aLayton, Robert | |
| 856 | 4 | 0 |
_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88853126 _qtext/html _a |
| 520 | _aThe next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis.This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems.There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK.Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations. | ||
| 999 |
_c69447 _d69447 |
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