Fine-Tuning ViT Classifier with Retina Images and Converting to ONNX - Video 3
Learn how to fine-tune a Vision Transformer (ViT) classifier using retinal images and convert it to ONNX format in this 12-minute video tutorial. Explore the process of adapting a pre-trained Google model, initially trained on the ImageNet 21k dataset, for Diabetic Retinopathy (DR) detection using the EyeQ dataset, a subset of the EyePacs dataset from the Kaggle Diabetic Retinopathy Detection competition. Follow along as the instructor demonstrates the fine-tuning process and guides you through converting the resulting model to ONNX format, enhancing its portability and deployment options. Access the accompanying Jupyter notebook on GitHub to practice and implement the techniques covered in this third installment of a four-part series on machine learning and data science.