Recommender System for Coursera Courses as part of the IBM Machine Learning Professional Certificate. In this project, several supervised and unsupervised machine learning algorithms (e.g. KNN, Logistic Regression, SVM, RandomForest, KMeans), and a Neural Network (tensorflow/keras) are employed to get new course recommendations for users based on Course Similarity or User Profile.
The streamlit library is used as frontend.
Simply clone this repo, setup a virtual environment and install the requirements:
pyenv local 3.9.8
python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install -r requirements.txt
Then, just start the streamlit app:
streamlit run PATH_TO_APP/recommender_app.py
in your CLI of choice to start the frontend in your default browser.