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4. Deep Learning with TensorFlow Datasets

  • 2021
  • OriginalPaper
  • Chapter
Published in:
Author
David Paper
Published in
State-of-the-Art Deep Learning Models in TensorFlow
Publisher
Apress

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Abstract

This chapter focuses on two comprehensive deep learning experiments using large and complex datasets. The first experiment involves classifying images of cats and dogs, while the second deals with images of human hands playing rock-paper-scissors. The chapter emphasizes the importance of data augmentation to improve model performance and generalization. It also includes practical steps for preprocessing data, building input pipelines, and training convolutional neural networks. The experiments are designed to be reproducible and provide insights into handling complex datasets and enhancing model performance through various techniques.
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previous chapter TensorFlow Datasets
next chapter Introduction to Tensor Processing Units
Title
Deep Learning with TensorFlow Datasets
Author
David Paper
Copyright Year
2021
Publisher
Apress
Book
State-of-the-Art Deep Learning Models in TensorFlow

Print ISBN: 978-1-4842-7340-1

Electronic ISBN: 978-1-4842-7341-8

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-1-4842-7341-8_4

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