Скачать или смотреть #7 Flights Price Predictor | Advanced Python Mini Project | For Intermediate

In this video, we are going to see about how to create flight price predictor in python.

We have used libraries like: flask, Sklearn, pickle and pandas to develop this python project.

The main motto is Predicting flight price from the previous time-series data using the best fitting model of machine learning algorithms with help of python and Django/flask framework. Training data has 10683 samples containing features like Airline name, Date of travel, Source, Destination, Departure and arrival time, Duration, Stops and Price of Flight. Similarly, 2671 samples are used for testing Random Forest Regression model. At last, flask is used as a framework for integrating model with frontends.

This project was challenging for me because all independent features were of categorical type. To convert it into numerical values LabelEncoder and OneHotEncoding were required. Numerous python concepts were used in the preprocessing stage.

For Source Code:
https://github.com/Sachinpatel95/Flig...
--OR--
https://github.com/Jasmin0600/Flight-...

LinkedIn Profile:
  / sachin-patel-eternal-guru-13552412a  

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