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 :)

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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
Video lie detector using xgboost - A video lie detector using OpenFace and xgboost

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Pytorch implemenation of Stochastic Multi-Label Image-to-image Translation (SMIT)

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Pytorch implementation of Masked Auto-Encoder

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Edge Restoration Quality Assessment

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Artificial Neural network regression model to predict the energy output in a combined cycle power plant.

Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu

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Duke Machine Learning Winter School: Computer Vision 2022

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Pytorch implementation of MaskFlownet

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Daniele Cattaneo 84 Nov 02, 2022
Exploring Simple 3D Multi-Object Tracking for Autonomous Driving (ICCV 2021)

Exploring Simple 3D Multi-Object Tracking for Autonomous Driving Chenxu Luo, Xiaodong Yang, Alan Yuille Exploring Simple 3D Multi-Object Tracking for

QCraft 141 Nov 21, 2022
g2o: A General Framework for Graph Optimization

g2o - General Graph Optimization Linux: Windows: g2o is an open-source C++ framework for optimizing graph-based nonlinear error functions. g2o has bee

Rainer Kümmerle 2.5k Dec 30, 2022
Example how to deploy deep learning model with aiohttp.

aiohttp-demos Demos for aiohttp project. Contents Imagetagger Deep Learning Image Classifier URL shortener Toxic Comments Classifier Moderator Slack B

aio-libs 661 Jan 04, 2023
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".

The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C

Wentao Xu 110 Dec 27, 2022
A small library for doing fluid simulation with neural networks.

Neural Fluid Fields This is a small library for doing fluid simulation with neural fields. Check out our review paper, Neural Fields in Visual Computi

Towaki 23 Jun 23, 2022
Flexible-CLmser: Regularized Feedback Connections for Biomedical Image Segmentation

Flexible-CLmser: Regularized Feedback Connections for Biomedical Image Segmentation The skip connections in U-Net pass features from the levels of enc

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Pytorch implementation of Decoupled Spatial-Temporal Transformer for Video Inpainting

Decoupled Spatial-Temporal Transformer for Video Inpainting By Rui Liu, Hanming Deng, Yangyi Huang, Xiaoyu Shi, Lewei Lu, Wenxiu Sun, Xiaogang Wang, J

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RLDS stands for Reinforcement Learning Datasets

RLDS RLDS stands for Reinforcement Learning Datasets and it is an ecosystem of tools to store, retrieve and manipulate episodic data in the context of

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TensorFlow implementation for Bayesian Modeling and Uncertainty Quantification for Learning to Optimize: What, Why, and How

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