Pinned Repositories
accelerate-rapids
CodePath
CodingTeaser
dask-mini-2019
drizzle-overview
Demo Drizzle ORM, Hono & Neon API
Flowise
Drag & drop UI to build your customized LLM flow
hpp-part1
hpp-part2
hpp-tools
RockStone's Repositories
RockStone/CodingTeaser
RockStone/accelerate-rapids
RockStone/CodePath
RockStone/dask-mini-2019
RockStone/drizzle-overview
Demo Drizzle ORM, Hono & Neon API
RockStone/Flowise
Drag & drop UI to build your customized LLM flow
RockStone/hpp-part1
RockStone/hpp-part2
RockStone/hpp-tools
RockStone/iFeel
iFeel app
RockStone/Mobile
mobile related
RockStone/lobe-chat
🤯 Lobe Chat - an open-source, modern-design LLMs/AI chat framework. Supports Multi AI Providers( OpenAI / Claude 3 / Gemini / Perplexity / Bedrock / Azure / Mistral / Ollama ), Multi-Modals (Vision/TTS) and plugin system. One-click FREE deployment of your private ChatGPT chat application.
RockStone/NextChat
Cross-platform Chat UI
RockStone/onnx
Open Neural Network Exchange
RockStone/rag-on-postgres
A RAG chat app on a PostgreSQL database
RockStone/sandbox
RockStone/sec-insights
A real world full-stack application using LlamaIndex
RockStone/stockpredictionai
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.