Learn how you can build advanced models yourself using Python and Tensorflow


In this course you’ll learn how to build and apply advanced Machine Models and Neural Networks for modelling the stochastic dynamical behaviour of assets prices and other time series.We cover the fundamental principles of Machine Learning, walk you through the most recent and exciting developments in Machine Learning that have unfolded over the last couple of years, share unpublished work and teach you how you can build these advanced models yourself using Python and Tensorflow.

After this course you will have:

  • a good understanding of the field of Machine Learning
  • know about the various models, methods and be aware of the dos and don’ts

Course Contents:

  • An overview of mathematical modelling principles
  • Modelling non-Gaussian densities
  • Simulating and forecasting complex dynamical behaviour based on real data – Outperform classical models like GARCH
  • Modelling implied volatility smiles elegantly
  • Reinforcement learning – from Blackjack to Asset Allocation
  • Unsupervised Learning – K means, Fixed Income, Volatility
  • Self Organizing Maps – Asset Classification and Diversification
  • Implementing non-linear variable reduction – Outperform PCA
  • Supervised Learning – A textual analysis example

Location: Central London, nearest underground station Marble Arch

Cost: £995+VAT