| 000 | a | ||
|---|---|---|---|
| 999 |
_c30936 _d30936 |
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| 008 | 230110b xxu||||| |||| 00| 0 eng d | ||
| 020 | _a9781138315068 | ||
| 082 |
_a006.312 _bROG |
||
| 100 | _aRogel-Salazar, Jesus | ||
| 245 | _aAdvanced data science and analytics with python | ||
| 260 |
_bCRC Press, _c2020 _aBoca Raton : |
||
| 300 |
_axxxv, 383 p. ; _bill., _c24 cm |
||
| 365 |
_b48.99 _cGBP _d104.60 |
||
| 490 | _aChapman & Hall/CRC data mining & knowledge discovery series | ||
| 504 | _aIncludes bibliographical references and index. | ||
| 520 | _aAdvanced Data Science and Analytics with Python enables data scientists to continue developing their skills and apply them in business as well as academic settings. The subjects discussed in this book are complementary and a follow up from the topics discuss in Data Science and Analytics with Python. The aim is to cover important advanced areas in data science using tools developed in Python such as SciKit-learn, Pandas, Numpy, Beautiful Soup, NLTK, NetworkX and others. The model development is supported by the use of frameworks such as Keras, TensorFlow and Core ML, as well as Swift for the development of iOS and MacOS applications. The book can be read independently from the previous volume and each of the chapters in this volume is sufficiently independent from the others providing flexibility for the reader. Each of the topics addressed in the book tackles the data science workflow from a practical perspective, concentrating on the process and results obtained. The implementation and deployment of trained models are central to the book. Time series analysis, natural language processing, topic modelling, social network analysis, neural networks and deep learning are comprehensively covered in the book. The book discusses the need to develop data products and tackles the subject of bringing models to their intended audiences. In this case literally to the users's fingertips in the form of an iPhone app. | ||
| 650 | _aDatabase Management | ||
| 650 | _aData mining | ||
| 650 | _aExploration de donnees | ||
| 650 | _aProgramming and Design | ||
| 650 | _aComputer program language | ||
| 650 | _aComputer Graphics | ||
| 650 | _aActivation function | ||
| 650 | _a Bayes' theorem | ||
| 650 | _aChain rule | ||
| 650 | _a Backpropogation | ||
| 650 | _aLSTM | ||
| 650 | _a Hidden layer | ||
| 650 | _aPandas | ||
| 650 | _aSocial network analysis | ||
| 650 | _aNatural language processing | ||
| 650 | _aNeural network | ||
| 942 |
_2ddc _cBK |
||