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Advanced data science and analytics with Python
"Advanced 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...
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| Auteur principal : | |
|---|---|
| Format : | Livre |
| Langue : | anglais |
| Titre complet : | Advanced data science and analytics with Python / Jesús Rogel-Salazar |
| Publié : |
Boca Raton :
CRC Press
, 2021 |
| Description matérielle : | 1 vol. (XXXV-383 p.) |
| Collection : | Chapman & Hall/CRC data mining and knowledge discovery series sous la dir. de Vipin Kumar |
| Sujets : |
| LEADER | 03087cam a2200397 4500 | ||
|---|---|---|---|
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| 005 | 20211025055600.0 | ||
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| 035 | |a (OCoLC)1280126921 | ||
| 073 | 1 | |a 9781138315068 | |
| 100 | |a 20211022h20202020k y0frey0103 ba | ||
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| 200 | 1 | |a Advanced data science and analytics with Python |f Jesús Rogel-Salazar | |
| 214 | 0 | |a Boca Raton |c CRC Press |d 2021 | |
| 215 | |a 1 vol. (XXXV-383 p.) |c ill., couv. ill. en coul. |d 22 cm | ||
| 225 | 2 | |a Chapman & Hall/CRC data mining and knowledge discovery series | |
| 320 | |a Bibiogr. p. [369]-378. Index | ||
| 330 | |a "Advanced 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" |2 4e de couverture | ||
| 359 | 2 | |b 1.No Time To Lose: Time Series Analysis |b 2.Speaking Naturally: Text and Natural Language Processing |b 3.Let Us Get Social: Graph Theory and Social Network Analysis |b 4.Thinking Deeply: Neural Networks and Deep Learning |b 5.Here Is One I Made Earlier: Machine Learning Deployment | |
| 410 | | | |0 127018697 |t Chapman & Hall/CRC data mining and knowledge discovery series |f sous la dir. de Vipin Kumar |c Boca Raton |n Chapman & Hall/CRC |d 2007- | |
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