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Mastering Machine Learning with Python in Six Steps : A Practical Implementation Guide to Predictive Data Analytics Using Python / by Manohar Swamynathan.

O'Reilly Online Learning: Academic/Public Library Edition Available online

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Format:
Book
Author/Creator:
Swamynathan, Manohar., Author.
Language:
English
Subjects (All):
Artificial intelligence.
Big data.
Open source software.
Computer programming.
Artificial Intelligence.
Big Data.
Open Source.
Local Subjects:
Artificial Intelligence.
Big Data.
Open Source.
Physical Description:
1 online resource (XXI, 358 p. 172 illus., 151 illus. in color.)
Edition:
1st ed. 2017.
Other Title:
Practical implementation guide to predictive data analytics using Python
Place of Publication:
Berkeley, CA : Apress : Imprint: Apress, 2017.
System Details:
text file
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.
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: Demystifying Neural Network
Chapter 7: Conclusion.
Notes:
Includes index.
ISBN:
9781484228661
1484228669
OCLC:
1017738611

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