Flight Price Prediction using Machine Learning
This is a Flask web app which predicts fare of Flight ticket on the bases of place of destination.
1.Real-World Impact: Helps travelers find cheaper flights, solving a common problem.
2.Complex Data: Involves handling diverse features like dates, seasons, demand, and routes.
3.Predictive Modeling: Challenges your machine learning skills by using time-series forecasting, regression models, or deep learning.
4.Dynamic Pricing: Deals with constantly changing airline prices, making prediction harder and more exciting.
5.Feature Engineering: Requires creativity to extract useful features from data like holidays, weather, and booking times.
6.Big Data Handling: Provides hands-on experience with large datasets from various airlines and travel platforms.
7.MLOps Practice: Involves deploying models that adapt to new data in real-time, aligning with your MLOps interests.
8.User-Focused: Offers a service that benefits a broad audience of frequent travelers.
9.Competitive Edge: Demonstrates your expertise in predictive analytics and pricing strategies.
10.Scalability: Can be extended to other domains like hotel prices or car rentals.
The Code is written in Python 3.6.10. If you don't have Python installed you can find it here. If you are using a lower version of Python you can upgrade using the pip package, ensuring you have the latest version of pip.