Introduction: We are spearheading a project aimed at leveraging AI to predict financial market trends. With the volatile nature of financial markets, our goal is to harness the power of data and cutting-edge AI techniques to provide real-time insights, guiding critical investment decisions. We've already taken substantial strides in data collection and storage as we transition to the modeling phase.
Technical Overview: Data Foundation: Through specialized APIs, we've amassed a rich set of data, including fundamental metrics, historical trends, technical indicators, news updates, and live market feeds. Database: All our structured and unstructured data resides in MongoDB, prepped and ready for AI processing. Multi Modeling Ambitions: Ludwig: We plan to utilize Ludwig due to its versatility. Specifically, we're interested in Sequence models (RNN, LSTM, GRU) for time-series analysis. Vision models (CNNs) for any graphical financial data. Combiners for integrating diverse data types. Tabular models (MLP) for structured data analytics. Text models (transformers) for deriving insights from news. Bard