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Deep Learning By Example

You're reading from   Deep Learning By Example A hands-on guide to implementing advanced machine learning algorithms and neural networks

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788399906
Length 450 pages
Edition 1st Edition
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Author (1):
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Ahmed Menshawy Ahmed Menshawy
Author Profile Icon Ahmed Menshawy
Ahmed Menshawy
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Table of Contents (18) Chapters Close

Preface 1. Data Science - A Birds' Eye View FREE CHAPTER 2. Data Modeling in Action - The Titanic Example 3. Feature Engineering and Model Complexity – The Titanic Example Revisited 4. Get Up and Running with TensorFlow 5. TensorFlow in Action - Some Basic Examples 6. Deep Feed-forward Neural Networks - Implementing Digit Classification 7. Introduction to Convolutional Neural Networks 8. Object Detection – CIFAR-10 Example 9. Object Detection – Transfer Learning with CNNs 10. Recurrent-Type Neural Networks - Language Modeling 11. Representation Learning - Implementing Word Embeddings 12. Neural Sentiment Analysis 13. Autoencoders – Feature Extraction and Denoising 14. Generative Adversarial Networks 15. Face Generation and Handling Missing Labels 16. Implementing Fish Recognition 17. Other Books You May Enjoy

Data Modeling in Action - The Titanic Example

Linear models are the basic learning algorithms in the field of data science. Understanding how a linear model works is crucial in your journey of learning data science because it's the basic building block for most of the sophisticated learning algorithms out there, including neural networks.

In this chapter, we are going to dive into a famous problem in the field of data science, which is the Titanic example. The purpose of this example is to introduce linear models for classification and see a full machine learning system pipeline, starting from data handling and exploration up to model evaluation. We are going to cover the following topics in this chapter:

  • Linear models for regression
  • Linear models for classification
  • Titanic example—model building and training
  • Different types of errors
...
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