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Python Data Analytics

With Pandas, NumPy, and Matplotlib

Paperback Engels 2018 9781484239124
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Samenvatting

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You'll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.
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

Specificaties

ISBN13:9781484239124
Taal:Engels
Bindwijze:paperback
Uitgever:Apress
Druk:2
Verschijningsdatum:28-9-2018

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Inhoudsopgave

Python Data Analytics
1. An Introduction to Data Analysis
2. Introduction to the Python's World
3. The NumPy Library
4. The pandas Library-- An Introduction
5. pandas: Reading and Writing Data
6. pandas in Depth: Data Manipulation
7. Data Visualization with matplotlib
8. Machine Learning with scikit-learn
9. Deep Learning with TensorFlow
10. An Example - Meteorological Data
11. Embedding the JavaScript D3 Library in IPython Notebook
12. Recognizing Handwritten Digits
13. Textual data Analysis with NLTK
14. Image Analysis and Computer Vision with OpenCV
Appendix A
Appendix B

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