This is a beginner-friendly repo to make a collection of some unique and awesome projects. Everyone in the community can benefit & get inspired by the amazing projects present over here.

Overview

Awesome-Projects-Collection

Quality over Quantity :)

DiscordLogo

What to do?

  1. Add some unique and amazing projects as per your favourite tech stack for the community to get benifitted. Add your projects under the respective tech stack folder only

  2. It can be any of any length and can be any number of scripts, just add a folder with your projects name.

  3. There is no need to raise an issue to add your project, you can directly raise a PR.

  4. While raising a PR, make sure to fill the description and checklist as per the description template following your project's specification & delete all the irrelevant checkboxes.

Update:

To resolve all the merge conflicts:

  1. Do not add your names in the contributor's list, we will do that on our own.

  2. Make sure to add a readme.md file with your project's description inside your project's folder. From now onwards, no need to add the project description in project_doc.md file, instead so as mentioned above.

What's next?

If there are some conflicts, just fetch upstream to update your remote repo and then raise PR.

Maintainer

Our hardworking Collaborators/Pull Request Reviewers

Our valuable Contributors

-[Your name](your-github_url or linkedlin-url) : Don't edit this template

All the best for Hacktoberfest :)

Owner
Rohan Sharma
Beta MLSA || Postman Student Expert || 5 star @ HackerRank || Java Developer || Open Source Enthusiast DTU'24
Rohan Sharma
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks

Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi

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Just playing with getting CLIP Guided Diffusion running locally, rather than having to use colab.

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SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data

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A certifiable defense against adversarial examples by training neural networks to be provably robust

DiffAI v3 DiffAI is a system for training neural networks to be provably robust and for proving that they are robust. The system was developed for the

SRI Lab, ETH Zurich 202 Dec 13, 2022
A multilingual version of MS MARCO passage ranking dataset

mMARCO A multilingual version of MS MARCO passage ranking dataset This repository presents a neural machine translation-based method for translating t

75 Dec 27, 2022
This repository contains a PyTorch implementation of "AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis".

AD-NeRF: Audio Driven Neural Radiance Fields for Talking Head Synthesis | Project Page | Paper | PyTorch implementation for the paper "AD-NeRF: Audio

551 Dec 29, 2022
Contains code for the paper "Vision Transformers are Robust Learners".

Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin

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(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin

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PyTorch implementation of MSBG hearing loss model and MBSTOI intelligibility metric

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