Kaggle The Home of Data Science – Anthony Goldbloom ODSC Boston 2015
Kaggle The Home of Data Science from odsc Keynote Presenter Bio Anthony Goldbloom is the founder and CEO of Kaggle. In 2011 & 2012, Forbes Magazine named Anthony as one of the 30 under 30 in technology, in 2013 the MIT Tech Review named him one... Read more
Data Science 101 – Todd Cioffi ODSC Boston 2015
Data Science 101 from odsc Curious about Data Science? Self-taught on some aspects, but missing the big picture? Well, you’ve got to start somewhere and this session is the place to do it. This session will cover, at a layman’s level, some of the basic concepts... 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... Read more
Learning to Love Bayesian Statistics – Allen Downey ODSC Boston 2015
http://tinyurl.com/lovebayes Bayesian statistical methods provide powerful tools for answering questions and making decisions. For example, the result of Bayesian analysis is a set of values and probabilties that can be fed directly into a cost-benefit analysis, which is not possible with conventional statistics. But there are... 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... Read more
Probabilistic Programming in Data Science – Thomas Wiecki ODSC Boston 2015
http://bit.ly/ThomasWieckiPresentation There exist a large number of metrics to evaluate the performance-risk trade-off of a portfolio. Although those metrics have proven to be useful tools in practice, most of them require a large amount of data and implicitly assume returns to be normally distributed. Bayesian modeling... Read more
Recurrent Neural Networks for Text Analysis – Alec Radford ODSC Boston 2015
Recurrent Neural Networks for Text Analysis from odsc Recurrent Neural Networks hold great promise as general sequence learning algorithms. As such, they are a very promising tool for text analysis. However, outside of very specific use cases such as handwriting recognition and recently, machine translation, they... 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... Read more
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... 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... Read more