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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.

The AsyncAPI specification allows you to create machine-readable definitions of your asynchronous APIs.

A streaming approach to JSON. Oboe.js speeds up web applications by providing parsed objects before the response completes.

OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.

Feather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow

Online collaborative Whiteboard that is simple, free, easy to use and to deploy

  • collaborative
  • javascript
  • whiteboard
  • teaching

:zap: RAN! React . GraphQL . Next.js Toolkit :zap: - SEO-Ready, Production-Ready, SSR, Hot-Reload, CSS-in-JS, Caching, CLI commands and more...