fastquant — Backtest and optimize your ML trading strategies with only 3 lines of code!

A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.

A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.

The aim is to understand which are the key factors for a certain level of credit risk to occur. In addition, some ML models capable to predict the credit risk level for a company in an year - given past years data - have been built and compared.

A series of interactive labs we prepared for the Chartered Financial Data Scientist Certification. The content of the series is based on Python, IPython Notebook, and PyTorch.

A Benchmark Dataset for Multimodal Scientific Fact Checking

Data Visualization with R and Python

This project involves exploratory data analysis and predictive modeling using various statistical and machine learning techniques. In the financial domain, we analyze the Weekly dataset, containing weekly returns spanning two decades. We aim to identify patterns and trends in the data, perform logistic regression, and compare different classificati