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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.
Shuffle: A general purpose security automation platform. Our focus is on collaboration and resource sharing.
- automation
- cybersecurity
- openapi
- shuffle
A robust & multipurpose Graph object for JavaScript & TypeScript.
- graph
A general purpose internationalization library in 292 bytes
A simple software rasterizer running on a WebGPU compute shader. Built for educational purposes.
Generate Scriptable app widget to query PurpleAir sensor and display local AQI.
Using the Dojo Toolkit for MVC JavaScript applications
Load popup, sidebar and background with JSDOM based on the manifest.json for testing purposes