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:<\/p>\n
- \n
- Introduce Computer Vision<\/li>\n
- Introduce convolutional layers into our models<\/li>\n
- Introduce the concept of regularisation<\/li>\n
- Introduce the validation set in training our model<\/li>\n
- Introduce how to save and reuse our model<\/li>\n<\/ul>\n
<\/a><\/p>\n
\n\nContents<\/strong><\/span><\/p>\n
Part 1: Deep Learning with TensorFlow 2.0<\/strong> (page 3)<\/span><\/p>\n
1. Introduction to the Notebooks 3<\/span><\/p>\n
2. Introduction to this Notebook 4<\/span><\/p>\n
- \n
- Loading the Libraries 4<\/span><\/li>\n
- Introduction to our problem 5<\/span><\/li>\n<\/ul>\n
3. Deep Learning Conceptual Introduction 5<\/span><\/p>\n
4. Data 7<\/span><\/p>\n
5. Model 12<\/span><\/p>\n
6. Training the Model 16<\/span><\/p>\n
7. Evaluation and Inference 20<\/span><\/p>\n
- \n
- Plotting our results 21<\/span><\/li>\n
- Making a prediction on a single image 23<\/span><\/li>\n<\/ul>\n
8. Summary 25<\/span><\/p>\n
9. Exercise 25<\/span><\/p>\n
Part 2: Computer Vision with CNNs<\/strong> (page 28)<\/span><\/p>\n
1. Introduction to this Notebook 28<\/span><\/p>\n
- \n
- Load Libraries 28<\/span><\/li>\n
- Loading our Data 29<\/span><\/li>\n<\/ul>\n
2. Data: Introduction to Computer Vision 29<\/span><\/p>\n
3. Model Building 32<\/span><\/p>\n
4. Training 36<\/span><\/p>\n
- \n
- Saving Models 39<\/span><\/li>\n
- Saving and Loading Weights Only 40<\/span><\/li>\n
- Saving and Loading an entire model 41<\/span><\/li>\n<\/ul>\n
5. Evaluation and Inference 41<\/span><\/p>\n
6. Summary 42<\/span><\/p>\n
7. Exercises 42\u00a0<\/span><\/p>\n
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- Saving and Loading Weights Only 40<\/span><\/li>\n
- Loading our Data 29<\/span><\/li>\n<\/ul>\n
- Making a prediction on a single image 23<\/span><\/li>\n<\/ul>\n
- Introduction to our problem 5<\/span><\/li>\n<\/ul>\n
- Loading the Libraries 4<\/span><\/li>\n