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Deep Learning Quick Reference

You're reading from  Deep Learning Quick Reference

Product type Book
Published in Mar 2018
Publisher Packt
ISBN-13 9781788837996
Pages 272 pages
Edition 1st Edition
Languages
Author (1):
Mike Bernico Mike Bernico
Profile icon Mike Bernico

Table of Contents (15) Chapters

Preface 1. The Building Blocks of Deep Learning 2. Using Deep Learning to Solve Regression Problems 3. Monitoring Network Training Using TensorBoard 4. Using Deep Learning to Solve Binary Classification Problems 5. Using Keras to Solve Multiclass Classification Problems 6. Hyperparameter Optimization 7. Training a CNN from Scratch 8. Transfer Learning with Pretrained CNNs 9. Training an RNN from scratch 10. Training LSTMs with Word Embeddings from Scratch 11. Training Seq2Seq Models 12. Using Deep Reinforcement Learning 13. Generative Adversarial Networks 14. Other Books You May Enjoy

Using Deep Learning to Solve Regression Problems

In this chapter, we will build a simple multilayer perceptron (MLP), which is a fancy name for a neural network with a single hidden layer, to solve a regression problem. Then we will go deeper with a deep neural network that has several hidden layers. Along the way, we will explore model performance and over fitting. So, let's get started!

We will cover the following topics in this chapter:

  • Regression analysis and deep neural networks
  • Using deep neural networks for regression
  • Building an MLP in Keras
  • Building a deep neural network in Keras
  • Saving and loading a trained Keras model
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