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The TensorFlow Workshop

You're reading from   The TensorFlow Workshop A hands-on guide to building deep learning models from scratch using real-world datasets

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781800205253
Length 600 pages
Edition 1st Edition
Languages
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Authors (4):
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Matthew Moocarme Matthew Moocarme
Author Profile Icon Matthew Moocarme
Matthew Moocarme
Abhranshu Bagchi Abhranshu Bagchi
Author Profile Icon Abhranshu Bagchi
Abhranshu Bagchi
Anthony Maddalone Anthony Maddalone
Author Profile Icon Anthony Maddalone
Anthony Maddalone
Anthony So Anthony So
Author Profile Icon Anthony So
Anthony So
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Toc

Table of Contents (13) Chapters Close

Preface
1. Introduction to Machine Learning with TensorFlow 2. Loading and Processing Data FREE CHAPTER 3. TensorFlow Development 4. Regression and Classification Models 5. Classification Models 6. Regularization and Hyperparameter Tuning 7. Convolutional Neural Networks 8. Pre-Trained Networks 9. Recurrent Neural Networks 10. Custom TensorFlow Components 11. Generative Models Appendix

6. Regularization and Hyperparameter Tuning

Activity 6.01: Predicting Income with L1 and L2 Regularizers

Solution:

  1. Open a new Jupyter notebook.
  2. Import the pandas library and use pd as the alias:
    import pandas as pd
  3. Create a list called usecols containing the column names AAGE, ADTIND, ADTOCC, SEOTR, WKSWORK, and PTOTVAL:
    usecols = ['AAGE','ADTIND','ADTOCC','SEOTR','WKSWORK', 'PTOTVAL']
  4. Create a variable called train_url that contains the URL to the training set:
    train_url = 'https://raw.githubusercontent.com/PacktWorkshops'\
                '/The-TensorFlow-Workshop/master/Chapter06'\
                '/dataset/census-income-train.csv'
  5. Load the training dataset into a DataFrame, train_data, using the read_csv() method. Provide the URL to the CSV file and the usecols...
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