Diabetic Retinopathy Detection with AI

Diabetic Retinopathy Detection with AI

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Learn to understand and implement Deep Neural Networks, Residual Nets, and Convolutional Neural Networks (CNNs) using Keras with TensorFlow 2.0, and evaluate their performance and generalization.

Key AI Functions:Computer Vision,Python Programming,Machine Learning,Deep Learning,Artificial Intelligence(AI)

Description for Diabetic Retinopathy Detection with AI

Features of Course

  • Develop an understanding of the theory and intuition that underlie Deep Neural Networks, Residual Nets, and Convolutional Neural Networks (CNNs).
  • Develop a deep learning model that utilizes Keras with Tensorflow 2.0 as a backend, utilizing Convolutional Neural Networks and Residual Blocks.
  • Evaluate the performance of the trained CNN and guarantee its generalization by employing a variety of key performance indicators.
  • Level: Intermediate

    Certification Degree: Yes

    Languages the Course is Available: 1

    Offered by: On Coursera provided by Coursera Project Network

    Duration: 2 hours learn at your own pace

    Schedule: Flexible

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