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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
On Demand Analytic and Learning Environments with Jupyter – Kyle Kelley and Andrew Odewahn ODSC Boston 2015
http://bit.ly/Odewahn_KelleyPresentation The Jupyter/IPython project has been building systems to enable collections of users to work on a shared system within their team, lab, and on a wide web audience. There is the multi user server JupyterHub, the temporary notebook system (tmpnb), blossoming Google Drive integration (jupyter-drive),... Read more
Adventures in Using R to Teach Mathematics – Paul Bamberg ODSC Boston 2015
Adventures in using R to teach mathematics from odsc In 2014 I launched a new course, “Mathematical Foundations of Statistical Software,” in the Harvard Extension school, aimed at students with a solid background in calculus. Lectures were a mixture of proofs and R scripts, all homework... Read more
A Hybrid Approach to Data Science Project Management – Elaine Lee ODSC Boston 2015
A Hybrid Approach to Data Science Project Management from odsc In recent years, Data Science evolved into its own profession as a response to the proliferation of data that needed to be analyzed and made actionable — a job that could not be adequately addressed by... Read more
Jumping to Conclusions – Richard Robehr Bijjani ODSC Boston 2015
Jumping to Conclusions from odsc Data Science is the study of the extraction of knowledge from data. What if we extract partial or inaccurate knowledge? This illusion of knowledge would lead us to make wrong decisions, with sometimes disastrous consequences such as in the case of... 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... 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
Vowpal Wabbit – Paul Mineiro ODSC Boston 2015
Vowpal Wabbit from odsc Vowpal Wabbit is both an open-source machine learning toolkit and an active research platform. In this talk I introduce Vowpal Wabbit, discuss some of the design decisions, and the types of problems for which VW is (or is not) a good fit.... 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