Crypto AI Analytics is a sophisticated desktop tool designed for data-driven crypto market analysis and intelligent trend detection.

Using Machine Learning for live currency trading

Official implementation of "Predicting Systemic Risk in Financial Systems Using Deep Graph Learning"

This is a model that has been trained on historical data obtained from Yahoo Finance. The data set comprises of all data records starting from the launch date of this stock in India (1996). This model aims to pick up key trends in the stock price fluctuations based on Time Series mapping. It is able to render predictions for the upcoming time period. The accuracy as obtained on the training data-set is about 90 percent and it successfully demonstrates key trends. It can be simulated on any stock in the market provided their historical data is made available. (One could use the yfinance API or download manually). Keras is used extensively along with Tensorflow for training. The model features 100 epochs of Base size 64. The training time depends on the hardware being used by the user. It is advisable to be performed on Google Colaboratory. For any issues/suggestions write to somshankar97@gmail.com

💱Machine Learning, Artificial Intelligence, Data Science for Finance💱

University project provided by Euklid, a company active in the data driven investment field that aim to manage savings and investments through thousands of different algorithms. The commodities analyzed are Gold, Oil, IBM, and NASDAQ

Machine Learning for French Stock Market Prediction

An end-to-end Automated ML pipeline for empirical asset pricing & DJI forecasting. Bridges econometric rigor with modern AI using H2O AutoML. Features include advanced preprocessing (Winsorization, ADF), statistical validation via the Diebold-Mariano test, and model explainability using SHAP values. Optimized for reproducible quantitative research.

Prêmio CFA Research Challenge / Prêmio Desafio Itaú Asset Quantamental / CFA Research Challenge Award / Itaú Asset Quantamental Challenge Award

finance machine learning projects

This project successfully demonstrates practical machine learning application in financial prediction, achieving exceptional accuracy while maintaining simplicity. The combination of robust data processing, intelligent feature engineering, and user-friendly application features creates a powerful tool for data-driven investment decisions.

📈 Forecast daily log-returns of the Dow Jones Industrial Average using an Automated Machine Learning pipeline that combines economic data and computational techniques.