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The Deep Learning with Keras Workshop

You're reading from   The Deep Learning with Keras Workshop Learn how to define and train neural network models with just a few lines of code

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Product type Paperback
Published in Jul 2020
Publisher Packt
ISBN-13 9781800562967
Length 496 pages
Edition 1st Edition
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Authors (3):
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Matthew Moocarme Matthew Moocarme
Author Profile Icon Matthew Moocarme
Matthew Moocarme
Mahla Abdolahnejad Mahla Abdolahnejad
Author Profile Icon Mahla Abdolahnejad
Mahla Abdolahnejad
Ritesh Bhagwat Ritesh Bhagwat
Author Profile Icon Ritesh Bhagwat
Ritesh Bhagwat
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Table of Contents (11) Chapters Close

Preface
1. Introduction to Machine Learning with Keras 2. Machine Learning versus Deep Learning FREE CHAPTER 3. Deep Learning with Keras 4. Evaluating Your Model with Cross-Validation Using Keras Wrappers 5. Improving Model Accuracy 6. Model Evaluation 7. Computer Vision with Convolutional Neural Networks 8. Transfer Learning and Pre-Trained Models 9. Sequential Modeling with Recurrent Neural Networks Appendix

2. Machine Learning versus Deep Learning

Activity 2.01: Creating a Logistic Regression Model Using Keras

In this activity, we are going to create a basic model using the Keras library. The model that we will build will classify users of a website into those that will purchase a product from a website and those that will not. To do this, we will utilize the same online shopping purchasing intention dataset that we did previously and attempt to predict the same variables that we did in Chapter 1, Introduction to Machine Learning with Keras.

Perform the following steps to complete this activity:

  1. Open a Jupyter notebook from the start menu to implement this activity. Load in the online shopping purchasing intention datasets, which you can download from the GitHub repository. We will use the pandas library for data loading, so import the pandas library. Ensure you have saved the csv files to an appropriate data folder for this chapter first. Alternatively, you can change...
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