Learn how to fine-tune a Vision Transformer (ViT) with a custom dataset in this 52-minute video tutorial, part of a 4-video series. Explore the process of using a pre-trained model by Google, initially trained on the ImageNet 21k dataset, and fine-tuning it with the EyeQ Dataset for Diabetic Retinopathy (DR) detection. Discover how to leverage the EyeQ Dataset, a subset of the EyePacs Dataset originally used in the Diabetic Retinopathy Detection Kaggle Competition. Access accompanying notebooks on GitHub to follow along and implement the techniques demonstrated in the video.
Fine-Tuning Vision Transformer for Diabetic Retinopathy Detection - Part 2
The Machine Learning Engineer via YouTube
Overview
Syllabus
LLMOPS :Fine Tune ViT classifier with retina Images. Detection Model #machinelearning #datascience
Taught by
The Machine Learning Engineer
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