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Automated Machine Learning with AutoKeras

You're reading from  Automated Machine Learning with AutoKeras

Product type Book
Published in May 2021
Publisher Packt
ISBN-13 9781800567641
Pages 194 pages
Edition 1st Edition
Languages
Author (1):
Luis Sobrecueva Luis Sobrecueva
Profile icon Luis Sobrecueva

Table of Contents (15) Chapters

Preface Section 1: AutoML Fundamentals
Chapter 1: Introduction to Automated Machine Learning Chapter 2: Getting Started with AutoKeras Chapter 3: Automating the Machine Learning Pipeline with AutoKeras Section 2: AutoKeras in Practice
Chapter 4: Image Classification and Regression Using AutoKeras Chapter 5: Text Classification and Regression Using AutoKeras Chapter 6: Working with Structured Data Using AutoKeras Chapter 7: Sentiment Analysis Using AutoKeras Chapter 8: Topic Classification Using AutoKeras Section 3: Advanced AutoKeras
Chapter 9: Working with Multimodal and Multitasking Data Chapter 10: Exporting and Visualizing the Models Other Books You May Enjoy

Visualizing the model

Now, we can view a little summary of the architecture for the best generated model:

model = clf.export_model()
model.summary()

Here is the output:

Figure 7.4 – Best model architecture summary

Figure 7.4 – Best model architecture summary

As we can see, AutoKeras, as we did in the classification example in Chapter 4, Image Classification and Regression Using AutoKeras, has chosen a convolution model (Conv1D) for this task. As we explained in the beginning of that chapter, this kind of architecture works really well when the order of the input sentences is not important for the prediction; there are no correlations between the different movie reviews.

Here is a visual representation of this:

Figure 7.5 – Best model architecture visualization graph

Figure 7.5 – Best model architecture visualization graph

As you already know, generating the models and choosing the best one is done by AutoKeras automatically, but let's explain these blocks in more detail.

Each block represents...

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