YoVDO

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

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
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

Related Courses

Neural Networks for Machine Learning
University of Toronto via Coursera
機器學習技法 (Machine Learning Techniques)
National Taiwan University via Coursera
Machine Learning Capstone: An Intelligent Application with Deep Learning
University of Washington via Coursera
Прикладные задачи анализа данных
Moscow Institute of Physics and Technology via Coursera
Leading Ambitious Teaching and Learning
Microsoft via edX