Introduction to machine learning with Python : a guide for data scientists / Andreas C. Müller and Sarah Guido.
Tipo de material:![Texto](/opac-tmpl/lib/famfamfam/BK.png)
- 9781449369415
- Machine learning with Python
- 005.133 23
Tipo de ítem | Biblioteca actual | Colección | Signatura topográfica | URL | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | |
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Biblioteca Digital UV General | General | Enlace al recurso | Disponible | |||||
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Ingeniería General | General | 005.133 M958i 2018 | Disponible | 00428548 |
Incluye índice.
Introduction -- Supervised learning -- Unsupervised learning and preprocessing -- Representing data and engineering features -- Model evaluation and improvement -- Algorithm chains and pipelines -- Working with text data -- Wrapping up.
Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination. You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. -- Provided by publisher.