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apachesparktutes

ar.js

Efficient Augmented Reality for the Web - 60fps on mobile!

aws-sagemaker-sentiment-analysis

ayoob7.github.io

cern-cms-muon-estimation-tasks

This is series of task done for the CERN CMS Muon estimation project

check-gh-repo-size

A program to check the size of a GitHub repo before cloning.

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

cluster-branch-program-in-java

A program to Cluster a set of Coordinate points

clustergan

Pytorch Implementation of ClusterGAN (arXiv:1809.03627)

deep-reinforcement-learning-nanodegree

Projects attempted in the Reinforcement Degree Nanodegree program

deeplearning-nanodegree-pytorch

A collection of notebooks and projects done as a part of Udacity's Deep Learning Nanodegree using Pytorch. https://www.udacity.com/course/deep-learning-nanodegree--nd101

dog_classification

A Nanodegree project for Deep Learning - udacity

english-interactive-dictionary-python

An Interactive Dictionary

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

facenet-face-recognition

This is the research product of the thesis manifold Learning of Latent Space Vectors in GAN for Image Synthesis. This has an application to the research, name a facial recognition system. The application was developed by consulting the FaceNet model.

fullstack-nanodegree-vm

generate_faces_gans

gnnpapers

Must-read papers on graph neural networks (GNN)

google-research

Google Research

hashing-functions-swift-playgrounds

This Swift Playground is about teaching Hashing Functions to students. I take through Hash Functions from 2 vantage points. They are File Comparisons and Hashed Lookups. These are the 2 ways that Hashing Functions are used.

hub

A library for transfer learning by reusing parts of TensorFlow models.

ieee

image-classification-templates

Templates from PyTorch for Deep Learning Tasks

iot-datathon-traffic-contraception

Traffic Contraception is a system that loads location based data from various different cities to get meaningful insights on traffic modelling and management. I take data handling from 2 vantage points. Visualization and Statistical modelling. Visualization is mandatory before performing machine learning operations or statistical modelling, and visualization help us familiarize with the data. After visualizing the data I modeled the data on statistical models. After modelling statistically the data was visualized on graphs for domain experts and city planners to analyze and make prudent changes to the traffic system. Such changes will have potentials to optimize the traffic flow thereby giving a better commute to load-intensive highways.

liquid-environments

Application made for the Visiting Student Research Program at KAUST

maze-robot-game

Maze Robot game made in the B programming language, using Atelier B and Pro B (Used Visual Studio Code B method plugin to develop)

neural-symbolic-machines

Neural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.

opencv

Open Source Computer Vision Library

openframeworks-clion

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