A Non-Autoregressive Transformer based Text-to-Speech, supporting a family of SOTA transformers with supervised and unsupervised duration modelings. This project grows with the research community, aiming to achieve the ultimate TTS

Pytorch implementation of CVPR2021 paper: SuperMix: Supervising the Mixing Data Augmentation

Code for experiments for "ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy"

A 'supervised' parser for Google Scholar

An open-source hyperspectral unmixing python package

Python-based toolkit for building and evaluating a transformer-based FAQ retrieval system

Flipper: Reproducing the FLIP protein benchmark results.

MLpronto is a tool for rapid, robust, and reproducible machine learning. No ML background is needed whatsoever.

Deep Learning sample code

A python implementation of the Twin Labeled LDA

Deploying the heart risk level predicting Regression model in a web application using Flask 💮

A few machine learning projects of mine.

Welcome to my machine learning journey repository! 🚀 Here, I document my learning ML experiences, projects, and insights as I progress through my B.Sc. CSIT program at Tribhuvan University, Nepal. Explore various machine learning algorithms and models, including supervised, unsupervised, and reinforcement learning.