Search Results for "brain"
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Showing 8 open source projects for "brain"
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Grafana: The open and composable observability platformGrafana is the open source analytics & monitoring solution for every database.
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Clipboard
Your new smart clipboard manager
Your second brain that remembers anything, anytime, anywhere. The Clipboard Project (CB for short) is the oh-so-awesome clipboard manager that's just like a second brain. It's fast and lightweight, feature-packed, and super user-friendly. Anyone can use CB - no matter who you are or what you're working on, from web developers to your Average Joe and even to your grandma. -
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type-challenges
Collection of TypeScript type challenges with online judge
...Each challenge is a miniature kata where you implement types that transform other types—parsing strings, inferring tuples, mapping unions—without writing any runtime code. Problems are arranged from warm-ups to brain-twisters, letting developers build intuition about distributive conditional types, inference in extends, variance, and other corner cases of the type system. The repository includes tests for each puzzle so you get immediate, compiler-driven feedback when your solution is correct. As a result, it doubles as both training material and a living reference for advanced patterns used in real libraries. ... -
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fastMRI
A large open dataset + tools to speed up MRI scans using ML
...It includes reference implementations for key MRI reconstruction architectures such as U-Net and Variational Networks (VarNet), along with example scripts for model training and evaluation using the PyTorch Lightning framework. The project also releases several fully anonymized public MRI datasets, including knee, brain, and prostate scans. -
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Brain AutoML
Google Brain AutoML
This repository contains a list of AutoML related models and libraries. Google Brain researchers have introduced a new way of programming automated machine learning (AutoML) based on symbolic programming. The researchers also proposed PyGlove, a general symbolic programming library for Python, to implement the symbolic formulation of AutoML. AutoML, designed to fill the machine learning industry’s talent gap, is gaining traction among various organizations. -
ScriptSure Cloud E-PrescribingScriptSure Cloud ERX allows users to electronically send prescriptions to all retail and mail order pharmacies attached to the Surescripts electronic network.
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Awesome Graph Classification
Graph embedding, classification and representation learning papers
A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers with reference implementations. Relevant graph classification benchmark datasets are available. Similar collections about community detection, classification/regression tree, fraud detection, Monte Carlo tree search, and gradient boosting papers with implementations. -
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Tensor2Tensor
Library of deep learning models and datasets
...Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. T2T was developed by researchers and engineers in the Google Brain team and a community of users. It is now deprecated, we keep it running and welcome bug-fixes, but encourage users to use the successor library Trax. -
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brain.js
GPU accelerated Neural networks in JavaScript for Browsers
GPU accelerated Neural networks in JavaScript for Browsers and Node.js. brain.js is a GPU accelerated library for Neural Networks written in JavaScript. Brain.js depends on a native module headless-go for GPU support. In most cases installing brain.js from npm should just work. However, if you run into problems, this means prebuilt binaries are not able to download from GitHub repositories and you might need to build it yourself. Brain.js is super simple to use. You do not need to know... -
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HYBRYD
Library written in C with Python API for IPv6 networking
...I'm trying to readapt it for Python 2.7.3 and GCC 4.6.3 The library has to be build as a simple Python extension using >python setup.py install and allows to create different kind of servers, clients or hybryds (clients-servers) over (TCP/UDP) using the Ipv6 Protocol. The architecture of the code is based on brain architecture. Will put an IPv6 adress active available as soon as possible so that you can download pieces of codes. The aim of that coding was to use primary linux commands easily codable and make an object of an IPv6 connection. Moreover, the model is full-state!
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