- Getting Started
- Getting Dataset
- Clean and Validate LADI Dataset
- PyTorch Data Loading
- Train and Test A Classifier
- Fine Tuning Torchvision Models - ResNet and AlexNet
- SageMaker - Build, Train, and Deploy ML Models
This documentation is about installing AWS tools and configuring AWS environment to download LADI dataset and load dataset in Python locally and remotely.
This folder contains dataset with 2000 images and labels.
Clean and Validate LADI Dataset
This documentation is about clean the LADI dataset. For this project, we have only extracted 2000 images for training.
This documentation is about loading LADI dataset in PyTorch framework including examples of writing custom Dataset, Transforms and Dataloader.
This documentation is about training and testing a classifier model using Convolutional Neural Network (CNN) from scratch.
Fine Tuning Torchvision Models
This documentation is about training and testing a classifier model using pre-trained ResNet and AlexNet.
SageMaker Build Train and Deploy ML Models
This documentation is about migrating model scripts into the AWS SageMaker environment.