Hong Kong Machine Learning Season 1 Episode 4

Simon did an introductory talk about deep learning techniques applied for natural language processing: CNNs, LSTMs, bi-LSTMs, CRF bi-LSTMs are networks often used to label sentences at the word, or even the character level. Tan did a visual introduction to Topological Data Analysis (TDA), the application of discrete topology to study point clouds. These techniques allow for a robust description of the point clouds properties at multiple scales via persistence diagrams. Robustness and persistence of patterns at multiple scales are a desirable properties, especially in the case of noisy and highly stochastic financial time series. Tan uses the persistence diagrams as features to a machine learning classifier (say XGBoost) to predict ETFs returns.