This repository is a running list of tutorials showcasing how Datmo helps users working with quantitative modeling projects (data science, machine learning, and artificial intelligence).
Prominent features addressed in the tutorials are as follows:
Experiment logging
snapshot create - Record fully comprehensive project state as a single unitProject visualization
snapshot ls - View all snapshots in the projectsnapshot diff - Compare differences/changes between two snapshotssnapshot inspect - See in-depth info about a single snapshotState recreation & reproducibility
snapshot checkout - Revert the project state to the version from a different snapshotrun - Run a containerized task for easy environment handlingEnvironment Handling
environment setup - Use one of our preconfigured environments, or bring your own!notebook - A streamlined way to spin up a Jupyter Notebookrstudio - A streamlined way to spin up RStudiojupyterlab - A streamlined way to spin up JupyterLabterminal - A streamlined way to enter a terminal inside the containerFor smaller examples with more isolated datmo feature demonstration, you can view the official core repository here.
| Project | Tags | Datmo Features |
|---|---|---|
| Kaggle Titanic Survivor Prediction (CLI / SDK in Jupyter Notebook) |
AutoML, TPOT, SVM | notebook, snapshot create, snapshot ls |
| Face Recognition (CLI in Jupyter Notebook) |
CV, dlib, face_recognition | notebook, snapshot create, snapshot ls |
| Keras Fashion MNIST (CLI in Jupyter Notebook) |
CV, keras, tensorflow | notebook, snapshot create, snapshot ls |
| Kaggle Jigsaw Toxic Comment Identification (CLI in Jupyter Notebook) |
NLP, capsule net, Keras | snapshot create, snapshot ls, env setup, notebook |
| Project | Tags | Datmo Features |
|---|---|---|
| Kaggle Otto Product Classification (CLI via R Notebook) |
grid search, XGBoost | snapshot create, snapshot ls |