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Courses>Programming Languages>Image Processing with Keras in Python
Data ScienceImage Processing with Keras in Python
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:advanced
Updated:26 February 2024
Published:08 September 2022
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Courses>Programming Languages>Image Processing with Keras in Python
Image Processing with Keras in Python
4 Hours
28716 students
Syllabus
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.
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.
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.
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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Careertail
Courses>Programming Languages>Image Processing with Keras in Python
Data ScienceImage Processing with Keras in Python
Price:Paid
Length:4 Hours
Language:English
Content type:video
level:advanced
Updated:26 February 2024
Published:08 September 2022
Similar courses
Opportunities
Courses>Programming Languages>Image Processing with Keras in Python
Image Processing with Keras in Python
4 Hours
28716 students
Syllabus
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.
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.
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.
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.
Similar courses
Opportunities
Make the most out of your online education
Careertail
Copyright © 2021 Careertail.
All rights reserved
Quick Links
Get StartedLog InAbout UsCourses
Company
BlogContactsPrivacy PolicyCookie PolicyTerms and Conditions
Stay up to date
Trustpilot