John Hearty - Python machine learning : unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics
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Abstract: Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data - its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the worlds leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Pylearn2, and featuring guidance and tips on everything from sentiment analysis to neural networks, youll soon be able to answer some of the most important questions facing you and your organization
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Leverage benefits of machine learning techniques using Python
A course in three modules
BIRMINGHAM - MUMBAI
Copyright 2016 Packt Publishing
All rights reserved. No part of this course may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this course to ensure the accuracy of the information presented. However, the information contained in this course is sold without warranty, either express or implied. Neither the authors, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this course.
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Published on: August 2016
Published by Packt Publishing Ltd.
Livery Place
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Birmingham B3 2PB, UK.
ISBN 978-1-78712-857-6
www.packtpub.com
Authors
Sebastian Raschka
David Julian
John Hearty
Reviewers
Richard Dutton
Dave Julian
Vahid Mirjalili
Hamidreza Sattari
Dmytro Taranovsky
Dr. Vahid Mirjalili
Jared Huffman
Ashwin Pajankar
Content Development Editor
Amrita Noronha
Production Coordinator
Arvindkumar Gupta
Machine learning and predictive analytics are becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace .It is one of the fastest growing trends in modern computing and everyone wants to get into the field of machine learning. In order to obtain sufficient recognition in this field, one must be able to understand and design a machine learning system that serves the needs of a project. The idea is to prepare a Learning Path that will help you to tackle the real-world complexities of modern machine learning with innovative and cutting-edge techniques. Also, it will give you a solid foundation in the machine learning design process, and enable you to build customized machine learning models to solve unique problems
, Python Machine Learning , discusses the essential machine algorithms for classification and provides practical examples using scikit-learn. It teaches you to prepare variables of different types and also speaks about polynomial regression and tree-based approaches. This module focuses on open source Python library that allows us to utilize multiple cores of modern GPUs.
, Designing Machine Learning Systems with Python , acquaints you with large library of packages for machine learning tasks. It introduces broad topics such as big data, data properties, data sources, and data processing .You will further explore models that form the foundation of many advanced nonlinear techniques. This module will help you in understanding model selection and parameter tuning techniques that could help in various case studies.
, Advanced Machine Learning with Python , helps you to build your skill with deep architectures by using stacked denoising autoencoders. This module is a blend of semi-supervised learning techniques, RBM and DBN algorithms .Further this focuses on tools and techniques which will help in making consistent working process.
, Python Machine Learning will require an installation of Python 3.4.3 or newer on Mac OS X, Linux or Microsoft Windows. Use of Python essential libraries like SciPy, NumPy, scikit-Learn, matplotlib, and pandas. is essential.
Before you start, Please refer:
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- We've added some additional notes to the code notebooks mentioning the offline datasets in case there are server errors. https://www.dropbox.com/sh/tq2qdh0oqfgsktq/AADIt7esnbiWLOQODn5q_7Dta?dl=0
- .
- , Advanced Machine Learning with Python, leverages openly available data and code, including open source Python libraries and frameworks.
This title is for Data scientist and researchers who are already into the field of Data Science and want to see Machine learning in action and explore its real-world application. Prior knowledge of Python programming and mathematics is must with basic knowledge of machine learning concepts.
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