Omkar Bhosale's starred repositories
build-your-own-x
Master programming by recreating your favorite technologies from scratch.
backend-challenges
A public list of open-source challenges from jobs around the world
caMicroscope
Digital pathology image viewer with support for human/machine generated annotations and markups.
mapbox-gl-native
Interactive, thoroughly customizable maps in native Android, iOS, macOS, Node.js, and Qt applications, powered by vector tiles and OpenGL
youtube-dl
Command-line program to download videos from YouTube.com and other video sites
complexPyTorch
A high-level toolbox for using complex valued neural networks in PyTorch
text_summurization_abstractive_methods
Multiple implementations for abstractive text summurization , using google colab
Awesome-Speech-Enhancement
A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.
spotify-downloader
Download your Spotify playlists and songs along with album art and metadata (from YouTube if a match is found).
ohmyzsh
🙃 A delightful community-driven (with 2,400+ contributors) framework for managing your zsh configuration. Includes 300+ optional plugins (rails, git, macOS, hub, docker, homebrew, node, php, python, etc), 140+ themes to spice up your morning, and an auto-update tool that makes it easy to keep up with the latest updates from the community.
summarization
Implementation of different summarization algorithms applied to legal case judgements.
Catch-A-Waveform
Official pytorch implementation of the paper: "Catch-A-Waveform: Learning to Generate Audio from a Single Short Example" (NeurIPS 2021)
NoiseTorch
Real-time microphone noise suppression on Linux.
Aditya-verma-youtube-playlist-code
This repo consists of aditya verma youtube channel code for different section.
Deep-Learning-for-Causal-Inference
Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.
Data-Scientist-Books
Data-Scientist-Books (Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Long Short Term Memory, Generative Adversarial Network, Time Series Forecasting, Probability and Statistics, and more.)