Image Processing with Keras in Python
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Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Course Description
Learn to Use Convolutional Neural Networks in Python
Image processing requires deep learning methods that use data to train neural
What You’ll Learn
Image Processing With Neural Networks
Convolutional neural networks use the data that is represented in images to learn. In this chapter, we will probe data in images, and we will learn how to use Keras to train a neural network to classify objects that appear in images.
Going Deeper
Convolutional neural networks gain a lot of power when they are constructed with multiple layers (deep networks). In this chapter, you will learn how to stack multiple convolutional layers into a deep network. You will also learn how to keep track of the number of parameters, as the network grows, and how to control this number.
Using Convolutions
Convolutions are the fundamental building blocks of convolutional neural networks. In this chapter, you will be introducted to convolutions and learn how they operate on image data. You will also see how you incorporate convolutions into Keras neural networks.
Understanding and Improving Deep Convolutional Networks
There are many ways to improve training by neural networks. In this chapter, we will focus on our ability to track how well a network is doing, and explore approaches towards improving convolutional neural networks.
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