Original): Lorentz Yeung
Originally published in the direction of artificial intelligence.
MCP 101 tutorial: build your own modular agent AI for information about investments in shares
Welcome to this tutorial McP 101! A short context of the project and began building AI systems for investments in shares in 2021 with a trading system based on the analysis of sentiments powered by XGBOOS. This system analyzed market moods from messages, social media and financial reports to predict shares and generate trade signals. He combined natural language processing (NLP) to assess sentiments, machine learning to recognize patterns and test yourself to validate strategy.
This tutorial shows the configuration and use of the MCP modular system called MCP (multi -component protocol), which integrates the progress in AI orchestration for the investment of action. The article includes framework components, necessary software installations and practical applications. It also emphasizes the functions of an AI flexible agent that can perform market queries in real time and arithmetic operations. Further instructions on starting the code and improving the system with additional functions, such as sentiments and XGBOOST integration, are in order to encourage the contribution and experiments from the community.
Read the full blog for free on the medium.
Published via AI
