World Business StrategiesServing the Global Financial Community since 2000

Day Two

09:00 – 10:00 – Lecture 5: From statistics to supervised machine learning

  • Bias-variance tradeoff
  • Under and over fitting

10:00 – 10:30 – Tutorial 5: Demo of bias-variance tradeoff

10:30 – 11:00 – Coffee break

11:00 – 12:00 – Lecture 6: Model and features selection

  • Cross-validation
  • Bootstrap
  • Regularization: shrinkage methods

12:00 – 12:30 – Tutorial 6: Demo of model selection for market impact assessment

12:30 – 13:30 – Lunch

13:30 – 14:30 – Lecture 7: Classification methods

  • Logistic regression
  • Decision Trees and Random Forests

14:30 – 15:00 – Tutorial 7: Solving classification problem and features selection by random forests

15:00 – 15:30 – Coffee break

15:30 – 16:30 – Lecture 8: Deep-learning

  • Optimization, gradient descend
  • Inference with Neural Networks: the theory
  • Feed-forward neural networks and backpropagation

16:30 – 17:00 – Tutorial 8: Construction of NN and backpropagation algorithm

  • Discount Structure
  • Super early bird discount
    25% until January 11th 2019

  • Early bird discount
    15% until February 1st 2019

  • Special Offer
    When two colleagues attend the 3rd goes free!

  • 70% Academic Discount
    (FULL-TIME Students Only)

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