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Python Data Analysis

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

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781789955248
Length 478 pages
Edition 3rd Edition
Languages
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Authors (2):
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Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
Avinash Navlani Avinash Navlani
Author Profile Icon Avinash Navlani
Avinash Navlani
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Toc

Table of Contents (20) Chapters Close

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

Summary

In this chapter, we discussed image processing using OpenCV. The main focus of the chapter was on basic image processing operations and face detection. The chapter started with an introduction to types of images and image color models. In later sections, the focus was on image operations such as drawing, resizing, flipping, and blurring an image. In the last section, we discussed face detection in a given input image

The next chapter, Chapter 14, Parallel Computing Using Dask, will focus on parallel computation on basic data science Python libraries such as Pandas, NumPy, and scikit-learn using Dask. The chapter will start with Dask data types such as dataframes, arrays, and bags. In later sections, we'll shift focus from dataFrames and arrays to delayed, preprocessing, and machine learning algorithms in parallel using Dask.

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