Supervised-ML---Simple-Linear-Regression---Newspaper-data. EDA and Visualization, Correlation Analysis, Model Building, Model Testing, Model predictions.

Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.

Conducted sentiment analysis and data visualization on YouTube comments using the TextBlob library, uncovering insights on audience engagement, emoji usage, and video performance metrics. Implemented linear regression models to explore correlations between views, likes, video titles, and audience engagement.

Pump-up the glam in Jupyter Notebooks with innovative tools like Plotly, MatPlotLib and Seaborn.

In this we have coded in python to get the regression equation and find the confidence interval and prediction interval.

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

Jupyter notebook, replicating studies on social capital from Nature journal, analyze economic connectedness, upward income mobility, and more. Python and relevant datasets are utilized to recreate figures and analyses.