Feature Engineering from odsc One of the most important, yet often overlooked, aspects of predictive modeling is the transformation of data to create model inputs, better known as feature engineering (FE). This talk will go into the theoretical background behind FE, showing how it leverages existing... Read more

Machine Learning for a Pet Insurance Company from odsc As an insurance company, we receive a monthly premium from policy holders and in return, we pay claims on veterinary bills. Insurance risk for pet health is relatively uncharted territory; identifying key patterns can affect the company... Read more

Uplift Modeling Workshop from odsc Traditional randomized experiments allow us to determine the overall causal impact of a treatment program (e.g. marketing, medical, social, education, political). Uplift modeling (also known as true lift, net lift, incremental lift) takes a further step to identify individuals who are... Read more

Can We Automate Predictive Analytics from odsc Recent news about the pending shortage of data scientists prompts speculation about automation: will machines replace human analysts? We propose a model of automation, and briefly review progress in automated machine learning over the past twenty years. Summarizing the... Read more

Machine Learning for Suits from odsc You will learn the basic concepts of machine learning – such as Modeling, Model Selection, Loss or Profit, overfitting, and validation – in a non-mathematical way, so that you can ask for data analysis and interpret the results of a... Read more

There exist a large number of metrics to evaluate the performance and risk of a trading strategy. Although those metrics have proven to be useful tools in practice, most of them require a large amount of data and yield unstable results on shorter timescales. Quantopian allows... Read more