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Fine-Tuning Vision Transformer Classifier for EyePacs Dataset Quality Model - Part 1

Offered By: The Machine Learning Engineer via YouTube

Tags

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

Course Description

Overview

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Dive into the world of fine-tuning Vision Transformers (ViT) with custom datasets in this 56-minute video tutorial, the first in a series of four. Learn how to leverage a pre-trained model by Google, initially trained on the ImageNet 21k dataset, and fine-tune it using the EyeQ Dataset for quality assessment purposes. Explore the EyeQ Dataset, a subset of the EyePacs Dataset originally used in the Diabetic Retinopathy Detection Kaggle Competition. Follow along with practical demonstrations and access the accompanying notebooks on GitHub to enhance your understanding of machine learning techniques for image classification tasks.

Syllabus

LLMOPS :Fine Tune ViT classifier EyePacs Dataset. Create and FineTune Quality Model #machinelerning


Taught by

The Machine Learning Engineer

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