Graph

Self-supervised Graph-level Representation Learning with Local and Global Structure

GraphLoG This project is an implementation of ‘Self-supervised Graph-level Representation Learning with Local and Global Structure’ in PyTorch, which is accepted as Short Talk by ICML 2021. We provide the pre-training and fine-tuning codes and also the pre-trained model on chemistry domain in this repository, and a more complete code version including the biology domain will be announced on the TorchDrug platform developed by MilaGraph group. Also, we would like to appreciate the excellent work of Pretrain-GNNs which lays a […]

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Computer Vision

A technology that adds computer-generated virtual content to real-world views through devices

Augmented Reality 101 The development of areas such as computer vision, image processing, and computer graphics, allow the introduction of technologies such as Augmented Reality. Azuma defines Augmented Reality as “a technology that adds computer-generated virtual content to real-world views through devices”. Introduction The purpose of these map is to give you an idea about Augmented Reality and to guide you through the main features that surround this technology. Read complete post in AR 101 — Augmented Reality. Definition and […]

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Deep Learning

A Mindmap summarising Machine Learning concepts from Data Analysis to Deep Learning

Machine Learning Mindmap / Cheatsheet A Mindmap summarising Machine Learning concepts, from Data Analysis to Deep Learning. Machine Learning is a subfield of computer science that gives computers the ability to learn without being explicitly programmed. It explores the study and construction of algorithms that can learn from and make predictions on data. Machine Learning is as fascinating as it is broad in scope. It spans over multiple fields in Mathematics, Computer Science, and Neuroscience. This is an attempt to […]

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Deep Learning

A server-client system that facilitates interactive medical image annotation by using AI

MONAI Label MONAI Label is a server-client system that facilitates interactive medical image annotation by using AI. It is an open-source and easy-to-install ecosystem that can run locally on a machine with one or two GPUs. Both server and client work on the same/different machine. However, initial support for multiple users is restricted. It shares the same principles with MONAI. Features The codebase is currently under active development. framework for developing and deploying MONAI Label Apps to train and infer […]

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Deep Learning

A deep learning based cutting-edge facial detector for Python coming with facial landmarks

RetinaFace RetinaFace is a deep learning based cutting-edge facial detector for Python coming with facial landmarks. RetinaFace is the face detection module of insightface project. The original implementation is mainly based on mxnet. Then, its tensorflow based re-implementation is published by Stanislas Bertrand. This repo is heavily inspired from the study of Stanislas Bertrand. Its source code is simplified and it is transformed to pip compatible but the main structure of the reference model and its pre-trained weights are same. […]

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Images

A Toolbox for Image Feature Matching and Evaluations

A Toolbox for Image Feature Matching and Evaluations In this repository, we provide easy interfaces for several exisiting SotA methods to match image feature correspondences between image pairs.We provide scripts to evaluate their predicted correspondences on common benchmarks for the tasks of image matching, homography estimation and visual localization. Notice This repository is expected to be actively maintained (at least before I graduate🤣🤣) and gradually (slowly) grow for new features of interest. Suggestions regarding how to improve this repo, such […]

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Machine Learning

Yolov5 + Deep Sort with PyTorch

Yolov5_DeepSort_Pytorch Real-time multi-object tracker using YOLO v5 and deep sort This repository contains a two-stage-tracker. The detections generated by YOLOv5, a family of object detection architectures and models pretrained on the COCO dataset, are passed to a Deep Sort algorithm which tracks the objects. It can track any object that your Yolov5 model was trained to detect. Before you run the tracker Clone the repository recursively: git clone –recurse-submodules https://github.com/mikel-brostrom/Yolov5_DeepSort_Pytorch.git If you already cloned and forgot to use –recurse-submodules you […]

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Python

Python News: What’s New From June 2021?

If you want to get up to speed on what happened in the world of Python in June 2021, then you’ve come to the right place to get your news! June was a month of change. Ewa Jodlowska, the Executive Director of the Python Software Foundation (PSF), announced her departure after serving for ten years, and the PSF Board of Directors gained three new directors. Let’s dive into the biggest Python news from the past month! Free Bonus: 5 Thoughts […]

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Beginner, Data Science, NLP, Python, Unstructured Data

A simple start with Natural Language Processing!

This article was published as a part of the Data Science Blogathon Introduction to NLP: After I got acquainted with Machine learning concepts, I was wary of venturing into NLP. To me, NLP was a subject area posing a complicated outlook. But after my first encounter with it, I have come to realize that though it is hard to master it, it is easy to follow the concepts. I am presenting some basic NLP concepts and their work. NLP or Natural […]

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NLP

FastText vs. Word2vec: A Quick Comparison

One of the questions that often comes up is what’s the difference between fastText and Word2Vec? Aren’t they both the same? Yes and no. They are conceptually the same, but there is a minor difference—fastText operates at a character level but Word2Vec operates at a word level. Why this difference? Before we dive into fastText , let’s quickly recap what Word2Vec is. With Word2Vec, we train a neural network with a single hidden layer to predict a target word based on its context (neighboring words). The assumption […]

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