A web-app built with streamlit to visualize and interact with machine learning models

CI/CD pipeline setup with Travis-CI. Running on a Docker container hosted on Heroku.

Polynomial Regression

Voronoi Tessellation

Running the Code

The above code can be run via the Dockerfile in the project's root directory with:

docker build -t modelweave ./
docker run -p 8080:8080 -itd --name modelweave modelweave

Alternatively, the code can be run via:

pip install -r requirements.txt
streamlit run app.py

Basic ML code was provided by Madhu G Nadig's repository

Name		Name	Last commit message	Last commit date
Latest commit History 96 Commits
data		data
images		images
.gitignore		.gitignore
.travis.yml		.travis.yml
A-Star.py		A-Star.py
Dockerfile		Dockerfile
K Means Clustering.py		K Means Clustering.py
K Nearest Neighbours.py		K Nearest Neighbours.py
Linear Regression.py		Linear Regression.py
Logistic Regression.py		Logistic Regression.py
Naive Bayes.py		Naive Bayes.py
README.md		README.md
Support Vector Machine.py		Support Vector Machine.py
app.py		app.py
heroku.yml		heroku.yml
logreg.py		logreg.py
polyreg.py		polyreg.py
requirements.txt		requirements.txt