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.
Fine-Tuning Vision Transformer Classifier for EyePacs Dataset Quality Model - Part 1
The Machine Learning Engineer via YouTube
Overview
Syllabus
LLMOPS :Fine Tune ViT classifier EyePacs Dataset. Create and FineTune Quality Model #machinelerning
Taught by
The Machine Learning Engineer
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