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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

Creating an email spam detector

The model we are going to create will detect spam emails from an emails dataset. This is a little dataset of 5,572 emails, labeled with a spam column.

The notebook with the complete source code can be found at the following link:

https://colab.research.google.com/github/PacktPublishing/Automated-Machine-Learning-with-AutoKeras/blob/main/Chapter05/Chapter5_SpamDetector.ipynb

Let's now have a look at the relevant cells of the notebook in detail, as follows:

  • Installing AutoKeras: As we commented in other examples, the following snippet at the top of the notebook is responsible for installing AutoKeras and its dependencies, using the pip package manager:
    !pip3 install autokeras
  • Importing needed packages: The following lines load tensorflow, pandas, numpy, and autokeras as needed dependencies for this project:
    import tensorflow as tf
    import pandas as pd 
    import numpy as np
    import autokeras as ak
    from sklearn import model_selection...
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