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Feature Engineering – David Epstein ODSC Boston 2015
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 data to produce... Read more
Machine Learning for a Pet Insurance Company – TJ Houk & David Jaw ODSC Boston 2015
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 in a big... Read more
Machine Learning Based Personalization Using Uplift Analytics: Examples and Applications – Victor Lo ODSC Boston 2015
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 truly positively influenced... Read more
Can We Automate Predictive Analytics – Thomas Dinsmore ODSC Boston 2015
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 current state of... Read more
Predictive Modeling Workshop – Max Kuhn ODSC Boston 2015
Predictive Modeling Workshop from odsc The workshop is an overview of creating predictive models using R. An example data set will be used to demonstrate a typical workflow: data splitting, pre-processing, model tuning and evaluation. Several R packages will be shown along with the caret package which provides a... Read more
Machine Learning for Suits – Rahul Dave ODSC Boston 2015
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 model in the... Read more
What Can Graphs Teach Us about Teachers: Using Graphs for High Quality Recommendations – Amit Bhattacharyya ODSC Boston 2015
What Can Graphs Teach Us about Teachers: Using Graphs for High Quality Recommendations from odsc Teachers Pay Teachers is an online marketplace for teachers to buy, sell and share original educational resources. As any marketplace grows, there is an increasing need to provide a customized experience so that the... Read more
Winning Data Science Competitions – Owen Zang ODSC Boston 2015
Owen Zhang is no stranger to data science competitions. He has competed in and won several high profile challenges, and is currently ranked 1st out of a community of 200,000 data scientists on Kaggle. This is an opportunity to learn the tips, tricks and techniques Owen employs in building... Read more
Quantifying Uncertainty: Evaluating Trading Algorithms using Probabilistic Programming ODSC Boston 2015
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 users to develop... Read more