Mastering machine learning with Python in six steps : a Practical implementation guide to predictive data analytics using Python By Manohar Swamynathan

By:

Swamynathan, Manohar

Material type: Text

TextSeries: Books for professionals by professionalsPublication details: Apress, c2017.Edition: 2nd EdDescription: i-xxi+358PISBN:

9781484240441

Subject(s):

Python (Computer program language) Data mining. Machine Learning

DDC classification:

005.133 SWA-M

Contents:

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: Deep and reinforcement learning-- Chapter 7: Conclusion.

Summary: 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.

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Holdings
Item type	Current library	Home library	Call number	Status	Date due	Barcode
Book	Dept. of Computational Biology and Bioinformatics Processing Center	Dept. of Computational Biology and Bioinformatics	005.133 SWA-M (Browse shelf(Opens below))	Available		DCB3969
Book	Dept. of Linguistics Processing Center	Dept. of Linguistics	005.133 SWA (Browse shelf(Opens below))	Available		LIN10640

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: Deep and reinforcement learning--
Chapter 7: Conclusion.

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.

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