Machine Learning Capstone Project

For Kaggle competition: https://www.kaggle.com/c/recursion-cellular-image-classification Background information: https://www.rxrx.ai/#the-data

The full Dataset for this project is available here: https://www.kaggle.com/c/recursion-cellular-image-classification/data Download and extract the full dataset to this directory - you should have a test and train folder with subfolders and images.

Main libraries used for this project:

Keras sklearn numpy pandas Tensorflow-gpu cv2 imgaug wandb (for logging and analysis)

Running the project

Make sure the above libraries are available. Using wandb is highly encouraged since training variables can easily be loaded from the config-defaults.yml file. However, it can be run by configuring the TrainingRunner in train-wb.py with the desired options.

To run the project using wandb, run this command from the command line after logging in with your wandb account (its free - sign up at www.wandb.com): wandb run python train-wb.py

The CSV files have been preprocessed and re-saved for ease of training and testing. When using the multi-generator, use: train_root.csv for training full data test_root.csv for testing train_controls_root.csv for using training control data all_controls_root.csv for using all control data