Flask-Course Project

[Model Link]- Here

This is a Flight Price Prediction Model build by using Flask and it's components.

Steps:

1. Cleaned and Preprocessed dataset and applied Pipeline, ColumnTransformer to apply all steps.
2. Followed Functional Programming Technique in Jupyter Notebook File.
3. Model Selection between different types of model and seeing the R2- Score(Accuracy) metric to select a model.
4. Model persistence(Saving the Model) using joblib.
5. Checking the Model first in Local Server and then Deploying it using Render(Cloud based app for deployment).

Libraries Used:

1. scikit-learn
2. feature-emgine
3. flask
4. flask-wtf
5. pandas
6. xgboost
7. joblib(for model creation) can also use pickle.
8. matplotlib.pyplot (can also use seaborn).