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Classification of COVID19 using Chest X-ray Images in Keras
  • Level Intermediate
  • Duration 3 hours
  • Offered by

About

In this 1 hour long project-based course, you will learn to build and train a convolutional neural network in Keras with TensorFlow as backend from scratch to classify patients as infected with COVID or not using their chest x-ray images. Our goal is to create an image classifier with Tensorflow by implementing a CNN to differentiate between chest x rays images with a COVID 19 infections versus without. The dataset contains the lungs X-ray images of both groups.We will be carrying out the entire project on the Google Colab environment. Please be aware of the fact that the dataset and the model in this project, can not be used in the real-life. We are only using this data for educational purposes. By the end of this project, you will be able to build and train the convolutional neural network using Keras with TensorFlow as a backend. You will also be able to perform data visualization. Additionally, you will also be able to use the model to make predictions on new data. You should be familiar with the Python Programming language and you should have a theoretical understanding of Convolutional Neural Networks. You will need a free Gmail account to complete this project. 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.

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This intermediate-level course, offered by Coursera, focuses on building and training a convolutional neural network using Keras and TensorFlow to classify COVID-19 from chest x-ray images. Ideal for IT and computer science enthusiasts, this 1-hour project-based course provides hands-on experience in a critical real-world application. Accessible for free, it caters to those looking to expand their skills in machine learning and healthcare technology.