Quantitative analysis, strategies and backtests

An implementation of iPhone X's FaceID using face embeddings and siamese networks on RGBD images.

Jupyter notebook tutorials from QuantConnect website for Python, Finance and LEAN.

Deep Learning with Catalyst

GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management

Приёмы в машинном обучении

Options Trader written in Python based off the ib_insync library.

An open source trading bot to leverage machine learning in the stock market

Samples and Exercises solved during the DataAnalisys courses from Mipt on coursera

Problem statement - Implement a solution to forecast stock 'volatility' following earnings calls release of S&P1500 companies.

ML basics

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…