Tutorials



Workshop - Data Visualization principles

June 9, 2017: Data Visualization Principles (Duncan Temple Lang)

In this workshop, we'll discuss best practices for displaying different types of static data. This is about designing data visualizations rather than the software and instructions we use to actually render them. We'll cover some basic principles to keep in mind …

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Workshop - Lessons from Binary Classification

In this second session, we will continue to explore machine learning with data driven examples.

Binary classification is the canonical machine learning task and its study has a rich history. Much of the main principles of machine learning have been discovered in this context. These principles continue to guide the …

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Workshop - Machine Learning

May 5 & 12, 2017: Machine Learning (James Sharpnack)

May 5: Part I - Lessons from Binary Classification: Overfitting and surrogate losses (James Sharpnack) Binary classification is the canonical machine learning task and its study has a rich history. Much of the main principles of machine learning have been discovered in this …

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Workshop - Efficient Code in R

April 28: Efficient Code in R (Duncan Temple Lang)

It is relatively easy to write R code quickly, but harder to write quick R code. We'll discuss some general strategies for writing faster R code and then explore R tools for finding bottlenecks in code and how to make these …

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Workshop - Python for data analysis 2

April 21: Overview of Python for Data Analysis, Part II (Nick Ulle)

This second of a two-part workshop will continue the hand on activities using popular Python packages to perform an end-to-end data analysis task.

Prerequisites: Attend the first session (April 14th).

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Workshop - Python for data analysis 1

April 14: Overview of Python for Data Analysis, Part I (Clark Fitzgerald)

This first of a two-part workshop will provide a high level overview of popular Python packages for scientific computing followed by hands on activities using these tools to perform an end-to-end data analysis task.

_Prerequisites: Come to the …

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