Flight-Fare-Prediction | end implementation and deployment of Machine Learning
kandi X-RAY | Flight-Fare-Prediction Summary
kandi X-RAY | Flight-Fare-Prediction Summary
Flight-Fare-Prediction is a Jupyter Notebook library. Flight-Fare-Prediction has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. You can download it from GitHub.
The Airline Flight Fare Prediction is a Flask web application to predict airline flight fares across the Indian cities. The dataset for the project is taken from Kaggle, and it is a time-stamped dataset so, while building the model, extensive pre-processing was done on the dataset especially on the date-time columns to finally come up with a ML model which could effectively predict airline fares across various Indian Cities. The dataset had many features which had to pre-processed and transformed into new parameters for a cleaner and simple web application layout to predict the fares. The various independent features in the dataset were:. Airline: The name of the airline. Date_of_Journey: The date of the journey. Source: The source from which the service begins. Destination: The destination where the service ends. Route: The route taken by the flight to reach the destination. Dep_Time: The time when the journey starts from the source. Arrival_Time: Time of arrival at the destination. Duration: Total duration of the flight. Total_Stops: Total stops between the source and destination. Additional_Info: Additional information about the flight. Price: The price of the ticket.
The Airline Flight Fare Prediction is a Flask web application to predict airline flight fares across the Indian cities. The dataset for the project is taken from Kaggle, and it is a time-stamped dataset so, while building the model, extensive pre-processing was done on the dataset especially on the date-time columns to finally come up with a ML model which could effectively predict airline fares across various Indian Cities. The dataset had many features which had to pre-processed and transformed into new parameters for a cleaner and simple web application layout to predict the fares. The various independent features in the dataset were:. Airline: The name of the airline. Date_of_Journey: The date of the journey. Source: The source from which the service begins. Destination: The destination where the service ends. Route: The route taken by the flight to reach the destination. Dep_Time: The time when the journey starts from the source. Arrival_Time: Time of arrival at the destination. Duration: Total duration of the flight. Total_Stops: Total stops between the source and destination. Additional_Info: Additional information about the flight. Price: The price of the ticket.
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Support
Flight-Fare-Prediction has a low active ecosystem.
It has 0 star(s) with 1 fork(s). There are 1 watchers for this library.
It had no major release in the last 6 months.
Flight-Fare-Prediction has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Flight-Fare-Prediction is current.
Quality
Flight-Fare-Prediction has no bugs reported.
Security
Flight-Fare-Prediction has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
Flight-Fare-Prediction is licensed under the GPL-3.0 License. This license is Strong Copyleft.
Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
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Flight-Fare-Prediction releases are not available. You will need to build from source code and install.
Installation instructions are not available. Examples and code snippets are available.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Flight-Fare-Prediction
Flight-Fare-Prediction Key Features
No Key Features are available at this moment for Flight-Fare-Prediction.
Flight-Fare-Prediction Examples and Code Snippets
No Code Snippets are available at this moment for Flight-Fare-Prediction.
Community Discussions
No Community Discussions are available at this moment for Flight-Fare-Prediction.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Flight-Fare-Prediction
You can download it from GitHub.
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