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Flight Fare Prediction

by kandikits Updated: Dec 5, 2022


Flight Fare Prediction is very useful for travel agencies as they can have an idea about the future fare trends and make their customers aware about them. This helps them to make decisions on whether to book flights for their clients or not. Flight Fare Prediction (having complex algorithms to calculate flight prices given various conditions present at that particular time) is a very interesting and useful project because it involves data analysis, machine learning and data science. We will use numpy for scientific computing with Python. It provides a rich array of tools such as linear algebra, Fourier transforms, statistical functions, and random number generation. Pandas to provide fast and flexible data structures for working with structured (tabular) data sets. joblib to provides tools to create shared memory jobs and implement lightweight pipelining in algorithmic code. kandi kit provides you with a fully deployable Flight Fare Prediction. Source code included so that you can customize it for your requirement.

Deployment Information

By using the below libraries you can create the Flight-Fare-Prediction. The entire solution is available as a package to download from the source code repository.

Download, extract and double-click kit installer file to install the kit. Note: Do ensure to extract the zip file before running it. Follow below instructions to deploy and run the solution. 1. Download the 'kit_installer.zip' then unzip the folder. 2. Then Double-tap the 'kit_installer' and then command prompt opens, when you're prompted during the installation of the kit, press Y to launch the app automatically. 3. To run the app manually, press N when you're prompted and locate the zip file Flight-Fare-Prediction.zip. 4. Extract the zip file and navigate to the directory Flight-Fare-Prediction. 5. Open command prompt in the extracted directory Flight-Fare-Prediction and run the command 'pip install -r requirements.txt' & 'python app.py'. 6. Running on local URL: http://127.0.0.1:5000/.

Development Environment

VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers.

vscodeby microsoft

TypeScript star image 130477 Version:1.66.2

License: Permissive (MIT)

Visual Studio Code

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vscodeby microsoft

TypeScript star image 130477 Version:1.66.2 License: Permissive (MIT)

Visual Studio Code
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jupyterby jupyter

Python star image 12379 Version:Current

License: Permissive (BSD-3-Clause)

Jupyter metapackage for installation, docs and chat

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jupyterby jupyter

Python star image 12379 Version:Current License: Permissive (BSD-3-Clause)

Jupyter metapackage for installation, docs and chat
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Exploratory Data Analysis

For extensive analysis and exploration of data, and to deal with arrays, these libraries are used. They are also used for performing scientific computation and data manipulation.

numpyby numpy

Python star image 20101 Version:v1.22.3

License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.

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numpyby numpy

Python star image 20101 Version:v1.22.3 License: Permissive (BSD-3-Clause)

The fundamental package for scientific computing with Python.
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python-ipyby autocracy

Python star image 479 Version:Current

License: Others (Non-SPDX)

IPy are a Python class and tools for handling of IPv4 and IPv6 addresses and networks. It is similar to Net::IP Perl module.

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python-ipyby autocracy

Python star image 479 Version:Current License: Others (Non-SPDX)

IPy are a Python class and tools for handling of IPv4 and IPv6 addresses and networks. It is similar to Net::IP Perl module.
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pandasby pandas-dev

Python star image 33259 Version:v1.4.1

License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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pandasby pandas-dev

Python star image 33259 Version:v1.4.1 License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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Data Visualization

The patterns and relationships are identified by representing data visually and below libraries are used for generating visual plots of the data.

matplotlibby matplotlib

Python star image 15355 Version:v3.5.1

License: No License (null)

matplotlib: plotting with Python

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matplotlibby matplotlib

Python star image 15355 Version:v3.5.1 License: No License

matplotlib: plotting with Python
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joblibby joblib

Python star image 2452 Version:Current

License: Permissive (BSD-3-Clause)

Computing with Python functions.

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joblibby joblib

Python star image 2452 Version:Current License: Permissive (BSD-3-Clause)

Computing with Python functions.
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flaskby pallets

Python star image 58462 Version:2.1.1

License: Permissive (BSD-3-Clause)

The Python micro framework for building web applications.

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flaskby pallets

Python star image 58462 Version:2.1.1 License: Permissive (BSD-3-Clause)

The Python micro framework for building web applications.
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Kit Solution Source

Flight-Fare-Predictionby divyansh1195

Jupyter Notebook star image 0 Version:Current

License: Strong Copyleft (GPL-3.0)

End to end implementation and deployment of Machine Learning Airline Flight Fare Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.

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Flight-Fare-Predictionby divyansh1195

Jupyter Notebook star image 0 Version:Current License: Strong Copyleft (GPL-3.0)

End to end implementation and deployment of Machine Learning Airline Flight Fare Prediction using python, flask, gunicorn, scikit-Learn, etc. on Heroku web application platform.
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Support

If you need help to use this kit, you can email us at kandi.support@openweaver.com or direct message us on Twitter Message @OpenWeaverInc .

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