A UI-based Data Science and Machine Learning toolkit that acts as a ready UI to perform all the major Data-science and Machine Learning operations, like, viewing the dataset statistics, and its information, performing EDA, data modification and cleaning operations, and visualization using different charts (say, line, bar, scatter, heatmap, box, etc.), model training, tuning, validation, evaluation, prediction, etc.
The idea behind this project was to accompany an industry client (say a user who may not know programming or details of ML implementation using a coding language) to perform a Supervised ML process in a fast, supported, and easy manner. The user of this toolkit can perform all the operations (right from browsing & importing the dataset to making predictions on the test set) just by clicking the buttons on the toolkit UI. In short, the user can perform all the main required operations of an ML model-building process, without having much programming knowledge (because all they will have to do is click on the buttons in that interactive UI).
The toolkit will help the clients to perform Machine Learning operations (without needing them to have any programming knowledge). Also, the users of this toolkit will be able to build and compare various models in less time.
- Learned the steps and procedure of a general ML process.
- Understood the concepts of application development.
- Learned how to create interactive UIs using a Python library.
- Implemented the created UI for the toolkit and verified the code.
- Developed a desktop version of the toolkit application.
- Studied APIs to create backend code for the web version.
- Designed the visual layout and workflow for the frontend UI of the web version.
- Learned Python-Flask to implement API functions.
- Learned Postman to verify these APIs.
- Developed the frontend design and backend API code for the web version of the toolkit application.
- Verified the workings of the toolkit.
