253 ratings
12,844 already enrolled
Build and train a convolutional neural network (CNN) using Keras
Display results and plot 2D spectrograms with Python in Jupyter Notebook
In this 1-hour long project-based course, you will learn the basics of using Keras with TensorFlow as its backend and use it to solve an image classification problem. The data we are going to use consists of 2D spectrograms of deep space radio signals collected by the Allen Telescope Array at the SETI Institute. We will treat the spectrograms as images to train an image classification model to classify the signals into one of four classes. By the end of the project, you will have built and trained a convolutional neural network from scratch using Keras to classify signals from space. 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. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - 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.
Deep Learning
Convolutional Neural Network
Machine Learning
Tensorflow
keras
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction and Import Libraries
Load and Preprocess SETI Data
Create Training and Validation Data Generators
Build the CNN Model
Learning Rate Scheduling and Compile the Model
Train the Model
Evaluate the 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 SS
Jun 13, 2020Good for people who already know the basics of deep learning and can work with CNNs.
by VS
Jan 1, 2023It's a nice course but it recommended that one must have knowledge of CNN and basic knowledge of python. If you think you are interested in radio astronomy you must go for it.
by HU
Apr 27, 2020good in handling the project ,step by step process
by GB
Jul 8, 2020Thanks very much to COursera and special thanks to our mentor Snehan Kekre
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.
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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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