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Mastering machine learning with Python in six steps : a practical implementation guide to predictive data analytics using Python /
Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps awa...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
[United States] :
Apress,
2017.
|
| Colección: | Books for professionals by professionals.
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Swamynathan, Manohar, |e author. | |
| 245 | 1 | 0 | |a Mastering machine learning with Python in six steps : |b a practical implementation guide to predictive data analytics using Python / |c Manohar Swamynathan. |
| 264 | 1 | |a [United States] : |b Apress, |c 2017. | |
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| 505 | 0 | |a Chapter 1: Getting Started in Python -- Chapter 2: Introduction to Machine Learning -- Chapter 3: Fundamentals of Machine Learning -- Chapter 4: Model Diagnosis and Tuning -- Chapter 5: Text Mining -- Chapter 6: Demystifying Neural Network -- Chapter 7: Conclusion. | |
| 520 | |a Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. This book's approach is based on the "Six degrees of separation" theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. You'll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you'll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage. | ||
| 506 | |a Access restricted to subscribing institutions. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Python (Computer program language) | |
| 650 | 0 | |a Data mining. | |
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| 650 | 4 | |a Python (Computer Program Language) | |
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| 650 | 4 | |a Computers |x Programming Languages |x Python. | |
| 650 | 6 | |a Python (Langage de programmation) | |
| 650 | 6 | |a Exploration de données (Informatique) | |
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| 650 | 7 | |a Python (Computer program language) |2 fast | |
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