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Machine Learning Using TensorFlow Cookbook

You're reading from   Machine Learning Using TensorFlow Cookbook Create powerful machine learning algorithms with TensorFlow

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Product type Paperback
Published in Feb 2021
Publisher Packt
ISBN-13 9781800208865
Length 416 pages
Edition 1st Edition
Languages
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Authors (3):
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Konrad Banachewicz Konrad Banachewicz
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Konrad Banachewicz
Luca Massaron Luca Massaron
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Luca Massaron
Alexia Audevart Alexia Audevart
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Alexia Audevart
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Table of Contents (15) Chapters Close

Preface 1. Getting Started with TensorFlow 2.x 2. The TensorFlow Way FREE CHAPTER 3. Keras 4. Linear Regression 5. Boosted Trees 6. Neural Networks 7. Predicting with Tabular Data 8. Convolutional Neural Networks 9. Recurrent Neural Networks 10. Transformers 11. Reinforcement Learning with TensorFlow and TF-Agents 12. Taking TensorFlow to Production 13. Other Books You May Enjoy
14. Index

Using the Keras Preprocessing API

The Keras Preprocessing API gathers modules for data processing and data augmentation. This API provides utilities for working with sequence, text, and image data. Data preprocessing is an essential step in machine learning and deep learning. It converts, transforms, or encodes raw data into an understandable, useful, and efficient format for learning algorithms.

Getting ready

This recipe will cover some preprocessing methods provided by Keras for sequence, text, and image data.

As usual, we just need to import TensorFlow as follows:

import tensorflow as tf
from tensorflow import keras
import numpy as np
from tensorflow.keras.preprocessing.sequence import TimeseriesGenerator, pad_sequences, skipgrams, make_sampling_table
from tensorflow.keras.preprocessing.text import text_to_word_sequence, one_hot, hashing_trick, Tokenizer
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense

We are ready to...

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