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Python Machine Learning Cookbook

You're reading from   Python Machine Learning Cookbook Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Length 642 pages
Edition 2nd Edition
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Authors (2):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Author Profile Icon Prateek Joshi
Prateek Joshi
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Toc

Table of Contents (18) Chapters Close

Preface 1. The Realm of Supervised Learning FREE CHAPTER 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Visualizing Data 6. Building Recommendation Engines 7. Analyzing Text Data 8. Speech Recognition 9. Dissecting Time Series and Sequential Data 10. Analyzing Image Content 11. Biometric Face Recognition 12. Reinforcement Learning Techniques 13. Deep Neural Networks 14. Unsupervised Representation Learning 15. Automated Machine Learning and Transfer Learning 16. Unlocking Production Issues 17. Other Books You May Enjoy

An introduction to data visualization

Data visualization is an important pillar of machine learning. It helps us to formulate the right strategies to understand data. The visual representation of data assists helps us choose the right algorithms. One of the main goals of data visualization is to communicate clearly by using graphs and charts.

We encounter numerical data all the time in the real world. We want to encode this numerical data by using graphs, lines, dots, bars, and so on, to visually display the information contained in those numbers. This makes complex distributions of data more understandable and usable. The process is used in a variety of situations, including comparative analysis, tracking growth, market distribution, public opinion polls, and much more.

We use different charts to show patterns or relationships between variables. We use histograms to display the...

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