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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.

papers about Face Detection; Face Alignment; Face Recognition && Face Identification && Face Verification && Face Representation; Face Reconstruction; Face Tracking; Face Super-Resolution && Face Deblurring; Face Generation && Face Synthesis; Face Transfer; Face Anti-Spoofing; Face Retrieval;

:cyclone: Clean Architecture with .NET6, C#10 and React+Redux. Use cases as central organizing structure, completely testable, decoupled from frameworks

  • solid-principles
  • ddd-architecture
  • clean-architecture
  • clean-code

Reusable, vendor-neutral, industry-specific, vendor-specific solution architecture patterns for enterprise

  • solutions-architect
  • solutions-engineering
  • enterprise-architecture
  • enterprise-software

A curated list of resources for Image and Video Deblurring

  • image-deblurring
  • video-deblurring
  • image-deconvolution
  • stereo-deblurring

An app showcasing Flutter components, with side-by-side source code view.

  • flutter
  • flutter-examples
  • flutter-demo
  • showcasing-flutter-components