Image Noise Reduction with Auto-encoders using TensorFlow
109 ratings

4,752 already enrolled
Develop an understanding of how Auto encoders work.
Be able to apply an auto encoder to reduce noise in given images.
109 ratings
4,752 already enrolled
Develop an understanding of how Auto encoders work.
Be able to apply an auto encoder to reduce noise in given images.
In this 2-hour long project-based course, you will learn the basics of image noise reduction with auto-encoders. Auto-encoding is an algorithm to help reduce dimensionality of data with the help of neural networks. It can be used for lossy data compression where the compression is dependent on the given data. This algorithm to reduce dimensionality of data as learned from the data can also be used for reducing noise in data. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Data Science
Deep Learning
Noise Reduction
Machine Learning
Autoencoder
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Importing Libraries
Data Preprocessing
Adding Noise
Building and Training a Classifier
Building the Autoencoder
Training the Autoencoder
Denoised Images
Composite Model
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
by NS
Aug 15, 2020nice presentation skill, it is helpful for me to noise reduction and image processing
by KO
Oct 11, 2020Teachable and Readable course.
Thanks so much!!
by NL
Apr 7, 2020Really great learning for beginners. Through project learning it gives very good confidence. But rhyme desktop should be available until completion of project.
by RB
Apr 16, 2020A nice and short project and a good way to built a simple autoencoder and neural network classifier and getting them up and running.
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
Guided Projects are not eligible for refunds. See our full refund policy.
Financial aid is not available for Guided Projects.
Auditing is not available for Guided Projects.
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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