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Neural Network Projects with Python

You're reading from   Neural Network Projects with Python The ultimate guide to using Python to explore the true power of neural networks through six projects

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789138900
Length 308 pages
Edition 1st Edition
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Author (1):
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James Loy James Loy
Author Profile Icon James Loy
James Loy
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Table of Contents (10) Chapters Close

Preface 1. Machine Learning and Neural Networks 101 2. Predicting Diabetes with Multilayer Perceptrons FREE CHAPTER 3. Predicting Taxi Fares with Deep Feedforward Networks 4. Cats Versus Dogs - Image Classification Using CNNs 5. Removing Noise from Images Using Autoencoders 6. Sentiment Analysis of Movie Reviews Using LSTM 7. Implementing a Facial Recognition System with Neural Networks 8. What's Next? 9. Other Books You May Enjoy

Other Python libraries

Besides pandas and Keras, we will also be using other Python libraries, such as scikit-learn and seaborn. scikit-learn is an open source machine learning library that is widely used in machine learning projects. The main functionality that we use in scikit-learn is to separate our data into a training and testing set during data preprocessing. seaborn is an alternative data visualization in Python that has been gaining traction recently. In the later chapters, we'll see how we can use seaborn to make data visualizations.

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