Fast & Simple Notes in Neovim 📃🚀
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47,133 repositories indexed
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Fast & Simple Notes in Neovim 📃🚀
Your second brain, inside Neovim.
R package for segmentation, registration and generating web-based brain atlases from microscope images
An Impressive Auto Layout DSL for iOS, tvOS & OSX. & It is written in pure swift.
The continuous feedback plugin for JetBrains IDEs
TensorFlow.Delphi (TF.Delphi) provides a Delphi(Pascal) Standard binding for TensorFlow. It aims to implement the complete Tensorflow API in Delphi which allows Pascal developers to develop, train and deploy Machine Learning models with the Pascal Delphi
Environment specific config generator for Dart and Flutter applications during CI/CD builds
Address book for computer vision models.
RootPainter: Deep Learning Segmentation of Biological Images with Corrective Annotation
🌈 burning rainbow bridge between your terminal and serial ports
Unofficial React SDK (React, React Native, Expo)
Friendly Environment for Neural Networks (fenn) is a simple Python framework for building ML/DL workflows and LLM agents faster, with prebuilt trainers, agent templates, logging, configuration management, and much more.
Modernized Pascal Anti-Grain Geometry
A macOS app to parse face landmarks from a video for training GANs
SneakyThrow is a Java library to ignore checked exceptions
This training kit has been developed to learn the basics of Backbone.JS.
brain-dead simple parallel processing for ruby
A multilayer perceptron network implemented in Go, with training via backpropagation.
A go library for easy configure and run command chains. Such like pipelining in unix shells.
pico sized functional library
Bundle allows you to create doctrine entities with fields that will be protected by encryption algorithms such as AES
A smart picker for Snacks.nvim that trains a neural network with your file picking preferences.
A package to simulate, filter, and estimate DSGE models with occasionally binding constraints
A flexible and general-purpose ngrams library written in Ruby. Raingrams supports ngram sizes greater than 1, text/non-text grams, multiple parsing styles and open/closed vocabulary models.