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Fine-Tuning Vision Transformer for Diabetic Retinopathy Detection - Part 2

Offered By: The Machine Learning Engineer via YouTube

Tags

Vision Transformers Courses Machine Learning Courses Deep Learning Courses Image Classification Courses Transfer Learning Courses Fine-Tuning Courses

Course Description

Overview

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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.

Syllabus

LLMOPS :Fine Tune ViT classifier with retina Images. Detection Model #machinelearning #datascience


Taught by

The Machine Learning Engineer

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