Flight ticket prices can be something hard to guess, today we might see a price, check out the price of the same flight tomorrow, it will be a different story. We might have often heard travelers saying that flight ticket prices are so unpredictable. As data scientists, we are gonna prove that given the right data anything can be predicted. Here you will be provided with prices of flight tickets for various airlines between the months of March and June of 2019 and between various cities.
Implementation:
i. Created a model that estimates Flight Prices to help users look for the best prices when booking flight tickets.
ii. Processed attributes from the Departure Time, Date of Journey, to quantify the data and make it more understandable.
iii. Optimized multiple Regression models using RandomGridsearchCV to reach the best model.
iv. Built a client-facing API using flask
v. Deployed app on AWS cloud server.
link: [login to view URL]
Note: For Web Framework Requirements: pip install -r [login to view URL]
Thats an interesting thing, I have done the same thing in fintech to predict the market share price in stock exchange. I find it easy for me i can build a hypothesis on the thing which you want.