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You're reading from Python Data Analysis Perform data collection, data processing, wrangling, visualization, and model building using Python

Product type Paperback

Published in Feb 2021

Publisher Packt

ISBN-13 9781789955248

Length 478 pages

Edition 3rd Edition

Languages

Python

Tools

Matplotlib

Concepts

Data Analysis

Authors (2):

Ivan Idris

Avinash Navlani

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Table of Contents (20) Chapters

Preface

1. Section 1: Foundation for Data Analysis

2. Getting Started with Python Libraries FREE CHAPTER

3. NumPy and pandas

4. Statistics

5. Linear Algebra

6. Section 2: Exploratory Data Analysis and Data Cleaning

7. Data Visualization

8. Retrieving, Processing, and Storing Data

9. Cleaning Messy Data

10. Signal Processing and Time Series

11. Section 3: Deep Dive into Machine Learning

12. Supervised Learning - Regression Analysis

13. Supervised Learning - Classification Techniques

14. Unsupervised Learning - PCA and Clustering

15. Section 4: NLP, Image Analytics, and Parallel Computing

16. Analyzing Textual Data

17. Analyzing Image Data

18. Parallel Computing Using Dask

19. Other Books You May Enjoy

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Technical requirements

This chapter has the following technical requirements:

You can find the code, face classifier file, and the datasets at the following Github link: https://github.com/PacktPublishing/Python-Data-Analysis-Third-Edition/tree/master/Chapter13 .
All the code blocks are available in the ch13.ipynb file.
This chapter uses .jpg/.jpeg files (google.jpg, image.jpg, messi.png, nature.jpeg, barcelona.jpeg, and tajmahal.jpg) for practice purposes.
This chapter uses one face classifier XML file (haarcascade_frontalface_default.xml).
In this chapter, we will use the OpenCV, NumPy, and matplotlib Python libraries.

The rest of the chapter is locked

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Authors (2)

Navlani

Avinash Navlani has over 8 years of experience working in data science and AI. Currently, he is working as a senior data scientist, improving products and services for customers by using advanced analytics, deploying big data analytical tools, creating and maintaining models, and onboarding compelling new datasets. Previously, he was a university lecturer, where he trained and educated people in data science subjects such as Python for analytics, data mining, machine learning, database management, and NoSQL. Avinash has been involved in research activities in data science and has been a keynote speaker at many conferences in India.

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Idris

Ivan Idris has an MSc in experimental physics. His graduation thesis had a strong emphasis on applied computer science. After graduating, he worked for several companies as a Java developer, data warehouse developer, and QA analyst. His main professional interests are business intelligence, big data, and cloud computing. Ivan Idris enjoys writing clean, testable code and interesting technical articles. Ivan Idris is the author of NumPy 1.5. Beginner's Guide and NumPy Cookbook by Packt Publishing.

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