Build a CNN Model for Retinal Image Diagnosis: TensorFlow & Keras tutorial

👁️ CNN Image Classification for Retinal Health Diagnosis with TensorFlow and Keras! 👁️

Welcome to our tutorial on building a Convolutional Neural Network (CNN) model to classify retinal images into four distinct categories.

In this step-by-step guide, you'll learn how to gather and preprocess a dataset of over 80,000 retinal images, design a powerful CNN architecture, and train a model that can accurately distinguish between these health categories.

🔥 What You'll Learn: ✅ Data Collection and Preprocessing: Discover how to acquire and prepare retinal images for optimal model training. ✅ CNN Architecture Design: Create a customized architecture tailored to retinal image classification. ✅ Training Process: Explore the intricacies of model training, including parameter tuning and validation techniques. ✅ Model Evaluation: Learn how to assess the performance of your trained CNN on a separate test dataset.

https://github.com/feitgemel/TensorFlowProjects/tree/master/Retinal%20OCT%20Images

More relevant content in this playlist : https://www.youtube.com/playlist?list=PLdkryDe59y4bxVvpexwR6PMTHH6_vFXjA

A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V 
I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ".
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