ML PlayGround for Regression Techniques

ML Playground to understand Linear and Logistic Regression

Features:

• Simulate linear and logistic regression on toy data
• Vizualize the model learning using optimizers, on a live plot

input_config.json

• Configuration file to select the Dataset, Regression Technique, Learning Rate, Loss Function, Classification Threshold and similar configurations critical for model selection and hyperparameters
• Select the relevant configuration and then run the ML_PlayGround_Regression.py file

Future Scope of Work:

• Code Enahncement
• Include Data pre-processing to scale data
• Implement weight initialization techniques
• Include more regression techniques, loss functions, optimizers
• JavaScript UI for the playground