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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.

:computer: :mortar_board: Learn Git and GitHub. Try the new desktop version →

Cookbook for Node on FHIR and the clinical Meteor.js build pipeline. Create FDA, HIPPA, and HL7 compliant Javascript/Node applications!

TranslatedFull-stack learning roadmap and Chinese tutorials for large language models (LLM)🔥: covers Prompt Engineering, RAG, AI Agent, MCP, fine-tuning, model deployment, Transformer, AI programming, and interviews at major tech companies, from beginner level to production practice.