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1,273–1,296 of 7,922 · Most stars

Task manager with Todoist, Nextcloud & CalDAV support designed for GNOME

  • vala
  • todoapp
  • todoist
  • todoist-api

Welcome to the home of the Hot Chocolate GraphQL server for .NET, the Strawberry Shake GraphQL client for .NET and Nitro the awesome Monaco based GraphQL IDE.

ClosedXML is a .NET library for reading, manipulating and writing Excel 2007+ (.xlsx, .xlsm) files. It aims to provide an intuitive and user-friendly interface to dealing with the underlying OpenXML API.

Advanced usage of UIAlertController and pickers based on it: Telegram, Contacts, Location, PhotoLibrary, Country, Phone Code, Currency, Date...

  • uialertcontroller
  • picker
  • image-picker
  • pickerview

Intelligent adaptive brightness for your external monitors

  • macos
  • macbook
  • display
  • adaptive-brightness

mlpack: a fast, header-only C++ machine learning library

  • machine-learning-library
  • c-plus-plus
  • deep-learning
  • nearest-neighbor-search

Claude skills for LinkedIn. 12 Claude Code and Codex skills that write human-sounding LinkedIn posts, craft comments that get noticed, analyze your feed, and build a publishing cadence, all from your terminal. Content engineering by Creative Content Crafts. MIT.

TranslatedNext generation Electron build tooling based on Vite. A new generation of Electron development and build tool that supports source code protection

Fawkes, privacy preserving tool against facial recognition systems. More info at https://sandlab.cs.uchicago.edu/fawkes

  • privacy-protection
  • privacy-enhancing-technologies
  • face-recognition
  • adversarial-machine-learning

Automatic HTTPS for any Go program: fully-managed TLS certificate issuance and renewal

  • https
  • acme
  • letsencrypt
  • golang

Plupload is JavaScript API for building file uploaders. It supports multiple file selection, file filtering, chunked upload, client side image downsizing and when necessary can fallback to alternative runtimes, like Flash and Silverlight.

  • plupload
  • file-upload
  • file-utility

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.