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🇫🇷 Oh my tmux! My self-contained, pretty & versatile tmux configuration made with ❤️
Applied Deep Learning Course
Code for 3D object detection for autonomous driving
Implementation of the methods described in "Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation", ECCV 2022
The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""
Using neural networks to identify glacier calving fronts from satellite imagery
A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets.
This repo contains code to convert Structured Documents to Graphs and implement a Graph Convolution Neural Network for node classification
iterative Linear Quadratic Regulator with constraints.
Find the best learning rate for a CNN with Keras. Source: www.pyimagesearch.com
A community-maintained Python framework for creating mathematical animations.
Minimal and clean examples of machine learning algorithms
BFSI sectors deal with lots of unstructured scanned documents which are archived in document management systems for further use.For example in Insurance sector, when a policy goes for underwriting, underwriters attached several raw notes with the policy, Insureds also attach various kind of scanned documents like identity card, bank statement, letters etc. In later parts of the policy life cycle if claims are made on a policy, releted scanned documents also archeived.Now it becomes a tedious job to identify a particular document from this vast repository. The goal of this case study is to develop a deep learning based solution which can automatically classify scanned documents.
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Official implementation of the paper "Segment Everything Everywhere All at Once"
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
A simple, rectangular self-organizing map with methods similar to clustering methods in Scikit Learn.
Solving the Traveling Salesman Problem using Self-Organizing Maps
Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters
Code for all my tutorials
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.