Overview
- Fully revised and updated with the latest tools and techniques for data analysis with Python
- Includes three new chapters on social media analysis, image analysis with OpenCV, and deep learning
- Written by IT Scientific Application Specialist, Fabio Nelli
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About this book
This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation
Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you've learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.
What You'll Learn
- Understand the core concepts of data analysis and the Python ecosystem
- Go in depth with pandas for reading, writing, and processing data
- Use tools and techniques for data visualization and image analysis
- Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch
Who This Book Is For
Experienced Python developers who need to learn about Pythonic tools for data analysis
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Table of contents (14 chapters)
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Bibliographic Information
Book Title: Python Data Analytics
Book Subtitle: With Pandas, NumPy, and Matplotlib
Authors: Fabio Nelli
DOI: https://doi.org/10.1007/978-1-4842-3913-1
Publisher: Apress Berkeley, CA
eBook Packages: Professional and Applied Computing, Apress Access Books, Professional and Applied Computing (R0)
Copyright Information: Fabio Nelli 2018
eBook ISBN: 978-1-4842-3913-1Published: 27 September 2018
Edition Number: 2
Number of Pages: XIX, 569
Number of Illustrations: 648 b/w illustrations
Topics: Python, Big Data, Artificial Intelligence