Dataset Preprocessing and ML Model Training Website Welcome to the Dataset Preprocessing and ML Model Training Website repository! This project is a web application designed to facilitate the uploading, preprocessing, and training of various machine learning models on user-provided datasets.
Features
Dataset Upload: Users can upload any dataset in CSV format.
Data Preprocessing: Automatic handling of missing values, normalization, and feature encoding.
Model Training: Train multiple machine learning models, including but not limited to:
Decision Trees Random Forests Support Vector Machines (SVM) AdaBoost
Model Evaluation: Evaluate the performance of the trained models using various metrics.
User Interface: Easy-to-use web interface for uploading datasets, selecting preprocessing options, and training models.
Technologies Used:
Frontend:
HTML, CSS, JavaScript
Backend:
Python Flask
Machine Learning:
Scikit-learn Pandas NumPy
Contributors:
Ashwin JR, Sanjay Jithesh, Fabio Sebastian, Sreeram A,