An Introduction to Machine Learning for Hackers
From Linear Regression to Logistic Regression
Date: This event took place live on September 18 2012
Presented by: John Myles White, Drew Conway
Duration: Approximately 60 minutes.
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We'll introduce programmers to two of the most common tools in the machine learning toolkit: linear regression and logistic regression. We'll show how these two tools let you make a first pass at solving almost any machine learning problem you might face.
About John Myles White
John Myles White is a Ph.D. student in the Princeton Psychology Department, where he studies how humans make decisions both theoretically and experimentally. Outside of academia, John has been heavily involved in the data science movement, which has pushed for an open source software approach to data analysis. He is also the lead maintainer for several popular R packages, including ProjectTemplate and log4r.
About Drew Conway
Drew Conway is a PhD candidate in Politics at NYU. He studies international relations, conflict, and terrorism using the tools of mathematics, statistics, and computer science in an attempt to gain a deeper understanding of these phenomena. His academic curiosity is informed by his years as an analyst in the U.S. intelligence and defense communities.