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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

Classification with TensorFlow

In the last chapter, we covered linear regression with TensorFlow, where we looked at both simple and multiple linear regression; we also explored various metrics for evaluating regression models. We concluded the chapter with a real-world use case, where we built a salary prediction model, and we used this to predict the salaries of new employees based on a set of features. In this chapter, we will continue with modeling in TensorFlow – this time, by exploring classification problems with TensorFlow.

We will start by looking at the concept of classification modeling, after which we will examine the various evaluation metrics for classification modeling and how we can apply them to various use cases. We will look at binary, multi-class, and multi-label classification modeling. Finally, we will walk through a case study, putting all we have learned into practice by building a binary classification model to predict whether a student will drop...

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