Overview
- Contains practical real-world examples of data analytics
- Covers a wide spectrum from basic statistics to ETL, deep learning and IoT
- Gives an idea of every technical aspect of an industrial analytics project
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Table of contents (7 chapters)
Keywords
About this book
After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects.
What You Will Learn
- Work with data analysis techniques such as classification, clustering, regression, and forecasting
- Handle structured and unstructured data, ETL techniques, and different kinds of databases such as Neo4j, Elasticsearch, MongoDB, and MySQL
- Examine the different big data frameworks, including Hadoop and Spark
- Discover advanced machine learning concepts such as semi-supervised learning, deep learning, and NLP
Who This Book Is For
Data scientists and software developers interested in the field of data analytics.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Advanced Data Analytics Using Python
Book Subtitle: With Machine Learning, Deep Learning and NLP Examples
Authors: Sayan Mukhopadhyay
DOI: https://doi.org/10.1007/978-1-4842-3450-1
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Sayan Mukhopadhyay 2018
eBook ISBN: 978-1-4842-3450-1Published: 29 March 2018
Edition Number: 1
Number of Pages: XV, 186
Number of Illustrations: 18 b/w illustrations
Topics: Python, Big Data, Open Source