Big Data, High-Frequency Data, and Machine Learning with kdb+/q Workshop
q is a programming language for array processing, developed by Arthur Whitney on the basis of Kenneth E. Iverson’s APL. The kdb+ database built on top of q is a de facto standard technology for dealing with rapidly arriving, high-frequency, big data.
kdb+/q has taken the world of electronic, including algorithmic, trading by storm. It is used by numerous sell-side and buy-side institutions, including some of the most successful hedge funds and electronic market makers.
Beyond the world of electronic trading, kdb+/q is used in retail, gaming, manufacturing, telco, IoT, life sciences, utilities, and aerospace industries.
Your course will take you through the foundations of kdb+/q and explain why it is a language of choice for Big Data, high-frequency data, and real-time event processing.
We shall explain how to work with tables and q-sql effectively, how to set up tickerplants, real-time, and historical instances, and how to apply kdb+/q to machine learning problems.
We shall consider advanced applications to tree-based regression and classification, random forests, deep learning, Google DeepMind and Monte Carlo search, producing demonstrations on real-life data examples.
This event is in conjunction with The Thalesians.
The Thalesians are a think tank of dedicated professionals with an interest in quantitative finance, economics, mathematics, physics and computer science, not necessarily in that order.