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…

Code for Machine Learning for Algorithmic Trading, 2nd edition.

Deep Learning Specialization by Andrew Ng on Coursera.

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.

Some Python Implementations of the Kalman Filter

A python library for time-series smoothing and outlier detection in a vectorized way.

High Frequency Market Making

Analyze documents with Amazon Textract and generate output in multiple formats.

High frequency trading (HFT) framework built for futures using machine learning and deep learning techniques

algorithmic trading backtest and optimization examples using order book imbalances. (bitcoin, cryptocurrency, bitmex, binance futures, market making)

Sample applications and demos for Document AI, the end-to-end document processing platform on Google Cloud

Feature engineering of a Limit Order Book. Extraction of features from a LOB in order to analyse the behaviour of trade market.

Feature Engineering and Feature Importance in Machine Learning for Financial Markets

Lesson material on data science and machine learning topics/concepts

API for identifying buffalos, elephants, rhinos, or zebras in African wildlife

Forecasting stock prices using Kalman Filter and Hidden Markov Models

Using the Mean-reversion strategy employing Kalman Filter code a strategy to trade Henry Hub Natural Gas Spot Price and West Texas Intermediate (WTI) Crude Oil Price