⚤👨👸 Ling is a Machine Learning Application using Flask Micro Web Framework and Naive Bayes Classifier which can predict the Gender of a person by just using the name of the person. Ling Application uses Machine Learning and Statistical Tools to build a model which can predict your Gender. The Application uses Naive Bayes Classifier and Scikit-Learn to develop the Model and the model is persisted using Pickle. A Flask Micro-Framework is used to create an Application Programming Interface (API) which accepts local HTTP Requests and deploy our Application.
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Flask Micro Web-Framework: Flask is a lightweight WSGI web application framework. It is designed to make getting started quick and easy, with the ability to scale up to complex applications. It began as a simple wrapper around Werkzeug and Jinja and has become one of the most popular Python web application frameworks. Flask offers suggestions, but doesn't enforce any dependencies or project layout. It is up to the developer to choose the tools and libraries they want to use. There are many extensions provided by the community that make adding new functionality easy. Reference.
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HTML and CSS: HTML is the standard markup language for Web pages. CSS stands for Cascading Style Sheets. It can control the layout of multiple web pages all at once.
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Naive Bayes Classifier: Naive Bayes is a probabilistic machine learning algorithm based on the Bayes Theorem, used in a wide variety of classification tasks.
The API for Ling has been developed on Swagger UI and can be viewed here.
This project is licensed under the MIT License - see the LICENSE file for details.