This is a sample project that ilustrates how to use MLflow and Jupyter to solve a classification problem.

1. Download the famous MNIST dataset from Kaggle and place then under the data folder.
2. Ensure you have installed jupyter,matplotlib, mlflow, pandas, numpy and sklearn on your python distribution.
3. Navigate to the root folder of this project and, using the console, run jupyter and MLflow:

• jupyter notebook
• mlflow ui

4. Open Jupyter on a brower tab. Most likely the URL would be something like http://localhost:8888/notebooks/MNIST data.ipynb.
5. Open MLflow on a different brower tab. In this case the URL would be something like http://127.0.0.1:5000/.
6. Run all the cells on the Jupter notebook: Top menu > Cells > Run all. Wait the notebook to complete.
7. Inspect the results of each of the experiments in the MLflow interface.