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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

5. Classification Models

Activity 5.01: Building a Character Recognition Model with TensorFlow

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 variable called file_url that contains the URL to the dataset:
    file_url = 'https://raw.githubusercontent.com/PacktWorkshops'\
              '/The-TensorFlow-Workshop/master/Chapter05'\
              '/dataset/letter-recognition.data'
  4. Load the dataset into a DataFrame() function called data using read_csv() method, provide the URL to the CSV file, and set header=None as the dataset doesn't provide column names. Print the first five rows using head() method.
    data = pd.read_csv(file_url, header=None)
    data.head()

    The expected output will be as follows:

    Figure 5.42: First five rows of the data

    You can see that the dataset contains 17 columns...

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