Making Open Work
May 8–9, 2017: Training & Tutorials
May 10–11, 2017: Conference
Austin, TX

Clean, analyze, and visualize data with R

Barbara Fusinska (Google)
5:05pm5:45pm Thursday, May 11, 2017
Data, Big and Small
Location: Ballroom F
Level: Intermediate
Average rating: ****.
(4.00, 3 ratings)

Who is this presentation for?

  • Software developers and data scientists

Prerequisite knowledge

  • A working knowledge of at least one programming language
  • A general familiarity with machine learning (useful but not required)

What you'll learn

  • Understand basic machine-learning concepts and how to use supervised and unsupervised learning algorithms
  • Explore R's capabilities for working with data and machine learning


Data science and machine learning are growing increasingly popular. R is an open source platform that offers numerous libraries and implementations of machine-learning algorithms, which makes it a perfect tool for exploratory data analysis and presenting the results of inquiries and data science in general.

Barbara Fusinska offers an introduction to machine learning and R’s capabilities in a field of data science. Along with the language basics, Barbara explores specific data applications built around common problems in supervised and unsupervised learning and demonstrates how to use R as a tool for data analysis, performing machine-learning computations, and displaying the results of predictions.

Photo of Barbara Fusinska

Barbara Fusinska


Barbara Fusinska is a machine learning engineer at Google. She has a strong software development background and is experienced in building diverse software systems. Barbara focuses on data science and big data and still enjoys programming as well. She believes in the importance of data and metrics when growing a successful business. Barbara is a frequent speaker at conferences.