Free Book: Deep Learning and Computer Vision with CNNs

Free Book: Deep Learning and Computer Vision with CNNs


By Dan Howarth and Ajit Jaokar, October 2019. 42 pages. Part 1 will introduce the core concepts of Deep Learning. We will also start coding straightaway with Tensorflow 2.0. In part 2, we use another dataset – the mnist dataset – to build on our knowledge. In particular, we will:

Introduce Computer Vision
Introduce convolutional layers into our models
Introduce the concept of regularisation
Introduce the validation set in training our model
Introduce how to save and reuse our model

Contents
Part 1: Deep Learning with TensorFlow 2.0 (page 3)
1. Introduction to the Notebooks 3
2. Introduction to this Notebook 4

Loading the Libraries 4
Introduction to our problem 5

3. Deep Learning Conceptual Introduction 5
4. Data 7
5. Model 12
6. Training the Model 16
7. Evaluation and Inference 20

Plotting our results 21
Making a prediction on a single image 23

8. Summary 25
9. Exercise 25
Part 2: Computer Vision with CNNs (page 28)
1. Introduction to this Notebook 28

Load Libraries 28
Loading our Data 29

2. Data: Introduction to Computer Vision 29
3. Model Building 32
4. Training 36

Saving Models 39
Saving and Loading Weights Only 40
Saving and Loading an entire model 41

5. Evaluation and Inference 41
6. Summary 42
7. Exercises 42 
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Link: Free Book: Deep Learning and Computer Vision with CNNs