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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

Introducing computer vision

Computer vision is a field that studies how to process, analyze, and understand the contents of visual data. In image content analysis, we use a lot of computer vision algorithms to build our understanding of the objects in the image. Computer vision covers various aspects of image analysis, such as object recognition, shape analysis, pose estimation, 3D modeling, visual search, and so on. Humans are really good at identifying and recognizing things around them! The ultimate goal of computer vision is to accurately model the human vision system using computers.

Computer vision consists of various levels of analysis. In low-level vision, we deal with pixel-processing tasks, such as edge detection, morphological processing, and optical flow. In middle-level and high-level vision, we deal with things such as object recognition, 3D modeling, motion analysis...

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