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TensorFlow Developer Certificate Guide

You're reading from   TensorFlow Developer Certificate Guide Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781803240138
Length 344 pages
Edition 1st Edition
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Author (1):
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Oluwole Fagbohun Oluwole Fagbohun
Author Profile Icon Oluwole Fagbohun
Oluwole Fagbohun
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Toc

Table of Contents (20) Chapters Close

Preface 1. Part 1 – Introduction to TensorFlow
2. Chapter 1: Introduction to Machine Learning FREE CHAPTER 3. Chapter 2: Introduction to TensorFlow 4. Chapter 3: Linear Regression with TensorFlow 5. Chapter 4: Classification with TensorFlow 6. Part 2 – Image Classification with TensorFlow
7. Chapter 5: Image Classification with Neural Networks 8. Chapter 6: Improving the Model 9. Chapter 7: Image Classification with Convolutional Neural Networks 10. Chapter 8: Handling Overfitting 11. Chapter 9: Transfer Learning 12. Part 3 – Natural Language Processing with TensorFlow
13. Chapter 10: Introduction to Natural Language Processing 14. Chapter 11: NLP with TensorFlow 15. Part 4 – Time Series with TensorFlow
16. Chapter 12: Introduction to Time Series, Sequences, and Predictions 17. Chapter 13: Time Series, Sequences, and Prediction with TensorFlow 18. Index 19. Other Books You May Enjoy

Summary

In this chapter, we discussed overfitting in image classification and explored the different techniques to overcome it. We started by examining what overfitting is and why it happens, and we discussed how we can apply different techniques such as early stopping, model simplification, L1 and L2 regularization, dropout, and data augmentation to mitigate against overfitting in image classification tasks. Furthermore, we applied each of these techniques in our weather dataset case study and saw, hands-on, the effects of these techniques on our case study. We also explored combining these techniques in a quest to build an optimal model. By now, you should have a good understanding of overfitting and how to mitigate it in your own image classification projects.

In the next chapter, we will dive into transfer learning, a powerful technique that allows you to leverage pre-trained models for your specific image classification tasks, saving time and resources while achieving impressive...

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