Data Science

Diabetic Retinopathy Detection with AI

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Coursera With GroupifyAI

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

  • 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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