Machine learning in data space web demo. Go to skdata.space for the live version.
In the tradition of Tkinter SVM GUI, the purpose of this app is to demonstrate how machine learning model forms are affected by the shape of the underlying dataset. By selecting a dataset or by creating one of your own, you can fit a model to the data and see how the model would make decisions based on the data it has been trained on. Although this is a toy example, hopefully it helps give you the intuition that the machine learning process is a model selection search for the best combination of features, algorithm, and hyperparameter that generalize well in a bounded feature space.
To run this app locally, first clone the repository and install the requirements:
$ pip install -r requirements.txt
You can then run the Flask app as follows:
$ python3 app.py
This will start a webserver for the app, you can open a browser window at http://127.0.0.1:5000/ to view the application.