This project predicts the admission of a student based on different features including university rating, student’s undergrade GPA, GRE score, research experience and etc. This predicts that how much chances are there that the student will get admission in his selected university or not.
In this project I have used multiple algorithms including linear regression, artificial neural network (ANN), random forest regressor, decision tree regressor. In the end I deployed Linear Regression model due to lack of storage on heroku. otherwise on local all models are working fine.
- tensorflow
pip install tensorflow - scikit-learn
pip install -U scikit-learn - flask
pip install flask - pickle
pip install pickle - matplotlib.pyplot
pip install matplotlib - seaborn
pip install seaborn - numpy
pip install numpy - pandas
pip install pandas
Download/clone this repository from this link: GitHub Repository in your system.
Open command line (anaconda prompt), go to the folder that contains all project files. Then run the command python app.py
which will give you an address like localhost:5000 or localhost:8050 copy that and paste it in the address bar of web browser.
Project's interface will load on the web browser.
Furthermore, I have deployed this project as web app on heroku. To visit that web app copy and paste this link in the address bar of web browser. Link: Heroku Web App
