Posts: Tutorial


DSI Workshop: Working with and Creating R Packages

Working with and Creating R Packages

Description:

This Data Science Initiative (DSI) workshop is all about R packages - both using them effectively, creating them for your own use, and how to create and publish packages for others. Packages can be used to simplify your own workflows by organizing and installing …

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Workshop: Data Visualization Principles

Data Visualization Principles

In this workshop led by DSI Director and Professor of Statistics Duncan Temple Lang, 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 …

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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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