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; she believes in the importance of data and metrics when growing a successful business. Barbara still enjoys programming as well. She is a frequent speaker at conferences. You can read more on her blog.