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Data Science  with Python

You're reading from   Data Science with Python Combine Python with machine learning principles to discover hidden patterns in raw data

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Product type Paperback
Published in Jul 2019
Publisher Packt
ISBN-13 9781838552862
Length 426 pages
Edition 1st Edition
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Authors (3):
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Rohan Chopra Rohan Chopra
Author Profile Icon Rohan Chopra
Rohan Chopra
Mohamed Noordeen Alaudeen Mohamed Noordeen Alaudeen
Author Profile Icon Mohamed Noordeen Alaudeen
Mohamed Noordeen Alaudeen
Aaron England Aaron England
Author Profile Icon Aaron England
Aaron England
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Toc

Table of Contents (10) Chapters Close

About the Book 1. Introduction to Data Science and Data Pre-Processing FREE CHAPTER 2. Data Visualization 3. Introduction to Machine Learning via Scikit-Learn 4. Dimensionality Reduction and Unsupervised Learning 5. Mastering Structured Data 6. Decoding Images 7. Processing Human Language 8. Tips and Tricks of the Trade 1. Appendix

Summary

In this chapter, we learnt how to create highly accurate structured data models and understood what XGBoost is and how to use the library to train models, Before we started, we were wondering what neural networks are and how to use the Keras library to train models. After learning about neural networks, we moved to handling categorical data. Finally, we learned what cross-validation is and how to use it.

Now that you have completed this chapter, you can handle any kind of structured data and creating machine learning models with it. In the next chapter, you will learn how to create neural network models for image data.

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