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Advanced Deep Learning with Python

You're reading from   Advanced Deep Learning with Python Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch

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Product type Paperback
Published in Dec 2019
Publisher Packt
ISBN-13 9781789956177
Length 468 pages
Edition 1st Edition
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Author (1):
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Ivan Vasilev Ivan Vasilev
Author Profile Icon Ivan Vasilev
Ivan Vasilev
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Core Concepts
2. The Nuts and Bolts of Neural Networks FREE CHAPTER 3. Section 2: Computer Vision
4. Understanding Convolutional Networks 5. Advanced Convolutional Networks 6. Object Detection and Image Segmentation 7. Generative Models 8. Section 3: Natural Language and Sequence Processing
9. Language Modeling 10. Understanding Recurrent Networks 11. Sequence-to-Sequence Models and Attention 12. Section 4: A Look to the Future
13. Emerging Neural Network Designs 14. Meta Learning 15. Deep Learning for Autonomous Vehicles 16. Other Books You May Enjoy

Summary

In this chapter, we explored the applications of deep learning in AVs. We started with a brief historical overview of AV research and we discussed the different levels of autonomy. Then we described the components of the AV system and identified when it's appropriate to use DL techniques. Next, we looked at 3D-data processing and PointNet. Then we introduced the topic of implementing driving policies using behavioral cloning, and we implemented an imitation learning example with PyTorch. Finally, we looked at Waymo's ChauffeurNet system.

This chapter concludes our book. I hope you enjoyed the read!

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