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Image Modeling with Keras
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Updated 05/2025Start Course for Free
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PythonArtificial Intelligence4 hours13 videos45 Exercises3,650 XP37,634Statement of Accomplishment
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Course Description
Learn to Use Convolutional Neural Networks in Python
Image model often requires deep learning methods that use data to train neural network algorithms to do various machine learning tasks. Convolutional neural networks (CNNs) are particularly powerful neural networks that you'll use to classify different types of objects for the analysis of images. This four-hour course will teach you how to construct, train, and evaluate CNNs using Keras.Turning images into data and teaching neural networks to classify them is a challenging element of deep learning with extensive applications throughout business and research, from helping an eCommerce site manage inventory more easily to allowing cancer researchers to quickly spot dangerous melanoma.
Discover Keras CNNs
The first chapter of this course covers how images can be seen as data, and how you can use Keras to train a neural network to classify objects found in images.The second chapter will cover convolutions, a fundamental part of CNNs. You’ll learn how they operate on image data and learn how to train and tweak your Keras CNN using test data. Later chapters go into more detail and teach you how to create a deep learning network.
Build Your Own Keras Neural Network
You’ll end the course by learning the different ways that you can track how well a CNN is doing and how you can improve their performance. At this point, you’ll be able to build Keras neural networks, optimize them, and visualize their responses across a range of applications.Prerequisites
Introduction to Deep Learning with Keras1
Image Processing With Neural Networks
2
Using Convolutions
3
Going Deeper
4
Understanding and Improving Deep Convolutional Networks
Image Modeling with Keras
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