you can add any codes in any language by creating its respective folder (if already not available).

Overview

HACKTOBERFEST-2021-WEB-DEV


Beginner-Hacktoberfest

Need Your first pr for hacktoberfest 2k21 ? come on in

About

This is repository of Responsive Portfolio for Hacktoberfest 2021. Participate in Hacktoberfest by contributing to any Open Source project on GitHub! Here is a starter project for first-time contributors.
Visit website


What's Hacktoberfest 2021?

Hacktoberfest is the easiest way to get into open source! Hacktoberfest is a month long festival of open source code presented by Digital Ocean and DEV this year in 2021.

During the entire month of October 2021, all you have to do is contribute to any open source projects and open at least 4 pull requests. Yes, any project and any kind of contributions. It can be a be a bug fix, improvement, or even a documentation change! And win a T-Shirt and awesome stickers.

If you’ve never contributed to open source before, this is the perfect time to get started because Hacktoberfest provides a large list of available contribution opportunities (and yes, there are always plenty for beginners too).



👕 Why Should I Contribute?

Hacktoberfest has a simple and plain moto.

Support open source and earn a limited edition T-shirt!

So, yes! You can win a T-Shirt and few awesome stickers to attach on your laptop. On plus side, you will get into beautiful world of open source and get the international exposure.
Wait there's more!



👍 This is Awesome! How Can I Contribute?

Don't know how to start of open source and Contribute to our Open Source Project ? Welcome to the world of hacking!

The steps to follow to contribute to any projects:

  1. If you don't have git on your machine, install it.

  2. Fork this repository

    Fork this repository by clicking on the fork button on the top of this page. This will create a copy of this repository in your account.

  3. Clone the repository

    Now clone the forked repository to your machine. Go to your GitHub account, open the forked repository, click on the code button and then click the copy to clipboard icon.

    Open a terminal and run the following git command:

    git clone "url you just copied"
    
  4. Add a upstream link to main branch in your cloned repo

    git remote add upstream <original repository>
    
  5. Keep your cloned repo upto date by pulling from upstream

    This will also avoid any merge conflicts while committing new changes

    git pull upstream main
    
  6. Create your feature branch

    Always create new branch

    git checkout -b <feature-name>
    
  7. Track your changes

    git add .
    
  8. Check for your changes.

    git status
    
  9. Commit all the changes

    Write commit message as "Small Message"

    git commit -m "Write a meaningfull but small commit message"
    
  10. Push the changes for review

    git push origin <branch-name>
    
  11. Create a PR on Github.

    Just hit the create a pull request button, you must write a PR message to clarify why and what are you contributing
    

🔥 What will happen after my contribution?

I have created a simple page to display all contributors list here, your name should appear shortly after the pull request is merged.


What I have to do?

You can add any codes in any language by creating its respective folder (if already not available).


Owner
Suman Sharma
We need to have a talk on the subject of what's yours and what's mine. [sumansharma101]
Suman Sharma
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space by Quande Liu, Cheng Chen, Ji

Quande Liu 178 Jan 06, 2023
Representing Long-Range Context for Graph Neural Networks with Global Attention

Graph Augmentation Graph augmentation/self-supervision/etc. Algorithms gcn gcn+virtual node gin gin+virtual node PNA GraphTrans Augmentation methods N

UC Berkeley RISE 67 Dec 30, 2022
A deep learning object detector framework written in Python for supporting Land Search and Rescue Missions.

AIR: Aerial Inspection RetinaNet for supporting Land Search and Rescue Missions AIR is a deep learning based object detection solution to automate the

Accenture 13 Dec 22, 2022
Trained on Simulated Data, Tested in the Real World

Trained on Simulated Data, Tested in the Real World

livox 43 Nov 18, 2022
Repository containing the PhD Thesis "Formal Verification of Deep Reinforcement Learning Agents"

Getting Started This repository contains the code used for the following publications: Probabilistic Guarantees for Safe Deep Reinforcement Learning (

Edoardo Bacci 5 Aug 31, 2022
QAT(quantize aware training) for classification with MQBench

MQBench Quantization Aware Training with PyTorch I am using MQBench(Model Quantization Benchmark)(http://mqbench.tech/) to quantize the model for depl

Ling Zhang 29 Nov 18, 2022
Using python and scikit-learn to make stock predictions

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

Robert Martin 1.3k Dec 29, 2022
Pytorch implementation of MixNMatch

MixNMatch: Multifactor Disentanglement and Encoding for Conditional Image Generation [Paper] Yuheng Li, Krishna Kumar Singh, Utkarsh Ojha, Yong Jae Le

910 Dec 30, 2022
DeepFashion2 is a comprehensive fashion dataset.

DeepFashion2 Dataset DeepFashion2 is a comprehensive fashion dataset. It contains 491K diverse images of 13 popular clothing categories from both comm

switchnorm 1.8k Jan 07, 2023
Benchmark tools for Compressive LiDAR-to-map registration

Benchmark tools for Compressive LiDAR-to-map registration This repo contains the released version of code and datasets used for our IROS 2021 paper: "

Allie 9 Nov 24, 2022
A Python library for unevenly-spaced time series analysis

traces A Python library for unevenly-spaced time series analysis. Why? Taking measurements at irregular intervals is common, but most tools are primar

Datascope Analytics 516 Dec 29, 2022
Convolutional Neural Network for 3D meshes in PyTorch

MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f

Rana Hanocka 1.4k Jan 04, 2023
Pretraining Representations For Data-Efficient Reinforcement Learning

Pretraining Representations For Data-Efficient Reinforcement Learning Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Ch

Mila 40 Dec 11, 2022
Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019)

Dynamic Multi-scale Filters for Semantic Segmentation (DMNet ICCV'2019) Introduction Official implementation of Dynamic Multi-scale Filters for Semant

23 Oct 21, 2022
Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021)

Towards Flexible Blind JPEG Artifacts Removal (FBCNN, ICCV 2021) Jiaxi Jiang, Kai Zhang, Radu Timofte Computer Vision Lab, ETH Zurich, Switzerland 🔥

Jiaxi Jiang 282 Jan 02, 2023
Multi Task RL Baselines

MTRL Multi Task RL Algorithms Contents Introduction Setup Usage Documentation Contributing to MTRL Community Acknowledgements Introduction M

Facebook Research 171 Jan 09, 2023
DeepDiffusion: Unsupervised Learning of Retrieval-adapted Representations via Diffusion-based Ranking on Latent Feature Manifold

DeepDiffusion Introduction This repository provides the code of the DeepDiffusion algorithm for unsupervised learning of retrieval-adapted representat

4 Nov 15, 2022
ilpyt: imitation learning library with modular, baseline implementations in Pytorch

ilpyt The imitation learning toolbox (ilpyt) contains modular implementations of common deep imitation learning algorithms in PyTorch, with unified in

The MITRE Corporation 11 Nov 17, 2022
The implementation for the SportsCap (IJCV 2021)

SportsCap: Monocular 3D Human Motion Capture and Fine-grained Understanding in Challenging Sports Videos ProjectPage | Paper | Video | Dataset (Part01

Chen Xin 79 Dec 16, 2022
SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning

Datasets | Website | Raw Data | OpenReview SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning Christopher

67 Dec 17, 2022