An Application for Data Science and Visualization made by students of the Master of Automation and IT program.
The application gives users a hands-on, user-friendly experience with data and includes a wide range of features like data manipulation, regression and classification, using artificial intelligence and machine learning.
To improve the application's usability, the user is given textual details about the methods being used, suggestions and tooltips for different user inputs, and graphical outputs.
- Data upload, selection and preview
- Perform smoothing, interpolation, outlier recognition on the selected dataset
- Classification and regression using artificial intelligence
- Classification and regression using machine learning
- Visual and graphical results
- Download the application files (as .zip from the repository and extract) into a folder on your system
- Open command prompt and change the working directory (use
cd [path to the folder]) to the application folder created above - Install the required libraries by typing
pip install -r requirements.txtin the command prompt - Run the application by typing
streamlit run About_The_Application.py
- Streamlit : Infrastructure of GUI and its related elements
- NumPy : Fundamental package for scientific computing
- pandas : Used for manipulation and analysis of dataframes
- matplotlib and seaborn : Basic libraries used to create graphical outputs
- scikit-learn : Library used to implement machine learning, and related methods
- TensorFlow : Used for AI based models and methods
- Yuganshu Wadhwa : User Interface
- Eduardo Guandulain : Data Smoothing
- Muhammad Munam Uddin Farooqui : Data Interpolation and Outlier Recognition
- Jan Schiefer : Classification and Regression using Artificial Intelligence (Source)
- Maximilian Brandt : Classification using Machine Learning
- Maryam Jahangir and Muhammad Ali : Regression using Machine Learning