Name: Yash
Type: User
Company: https://next-portfolio-sand-zeta.vercel.app/
Bio: Always trying to learn new and exciting things.
Techy, Data Structures and Algorithms,
working on opencv, deep learning, NLP projects.
Location: New Delhi
Blog: https://www.youtube.com/channel/UCcn5IarvUW_rz_asszmn2bQ
Yash's Projects
This is the official website of our work 3D Appearance Super-Resolution with Deep Learning published on CVPR2019.
Deep Learning – Artificial Neural Network Using TensorFlow In Python
A place to save your everyday use code snippets and the ability to share them with your colleagues/friends/collaborators.
In this repo, i will be uploading solutions of various questions asked in interviews with the question name as the file name.
projects on deep learning, state of the art models
In this repository, I have implemented several state-of-the-art computer vision tasks using Detectron 2.
A neural network to generate captions for an image using CNN and RNN with BEAM Search.
Image Captioning: Implementing the Neural Image Caption Generator with python
A fullstack chat app made using react native and firebase.
Supervised and Unsupervised machine learning algorithms and related projects.
Our college major project in which we will be building a website (mainly be focusing on the backend part i.e. Python, Data Science) which provides all the Medical Solution in one place.
I created an end to end Movie Recommendation system using React as frontend and python FLASK as backend server.
In this repo I will be creating a series of videos (on my youtube channel) on Neural Networks from scratch, and the scripts will be saved here!
creating awesome artifects with the help of deep learning and artificial neural networks
A Nike mobile app clone using expo-router
In this repository, i will be making some cool projects in NLP from basic to intermediate level.
Open Source Computer Vision Library
From detection to Recognition
⚡ Competitive Programming Library
In this project, i have implemented yolov3-tiny to detect person and then apply an algorithm to find eucledian distance between centroids of detected people and based on this distance classify them as infected or not.
Led-Dot-Matrix