RALTIN

Many institutional investors spend an inordinate time developing features to feed into their machine learning models. As Andrew Ng, the co-founder of Google Brain, said - "Coming up with features is difficult, time-consuming, requires expert knowledge. "Applied machine learning" is basically feature engineering."... Raltin's cross functional team of software engineers, data scientists, and financial domain experts have developed the most comprehensive set of features for your machine learning models... Features that cannot be developed in house: Some features such as correlations across the entire equity and options universe require running billions of correlations and are not possible to run in house because of computing costs and engineering resources.