PyTorch implementations of the beta divergence loss.

Implementation of the paper "On the Asymptotic Mean Square Error Optimality of Diffusion Models."

Implementation of two new protocols in the Shuffle Model of Differential Privacy for the private summation of vector-valued messages

Super Resolution's the images by 3x using CNN

Comparison of common loss functions in PyTorch using MNIST dataset

This project is designed to extract sales data from a PostgreSQL database, process it, and use a Random Forest model to predict sales quantities. It also visualizes real and predicted sales for better understanding.

Python images vector quantizer lossy compressor and decompressor.

Calculates and visualizes the temporal domain and frequency domain mean squared error of ffmpeg audio filters

This code demonstrates how to integrate Apache Beam with scikit-learn datasets and perform simple data transformations. It loads the Linnerud dataset from scikit-learn, converts it into a Pandas DataFrame for easier manipulation.

Integrating the diffusion model-based MSE-optimal denoising strategy into the diffusers pipeline.

This project provides tools to search for datasets on Kaggle, download and preprocess them, and perform predictions using a Linear Regression model. It includes interactive text-based user interfaces built with `curses`.

Implementation of Gradient Descent that trains a linear regression model.

Performing gradient descent for calculating slope and intercept of linear regression using sum square residual or mean square error loss function.

Python images scalar quantizer lossy compressor and decompressor.

This research project explores the correlation between lifestyle choices and sleep efficiency, with the goal of creating a predictive model for sleep efficiency based on individual lifestyle factors. The project will employ a regression model derived from the field of Mathematical Modeling.

An introduction to machine learning

Using Collaborative Filtering predicting Movie Rating and K-nearest Neighbours & SVM algorithms for Number ClassificationNumber Classification