With the increasing availability of data and easy to use open source tools, Machine Learning and Data Visualization have become more accessible. As a result, they are now key factors in any data-driven process or organization in a wide range of domains.

The workshop will have two parts: The first will provide a  hands-on experience of Machine Learning and Deep Learning methods using a set of Jupyter notebooks in Python. Participants will be guided through different concrete use cases and approaches to demonstrate the potential of Machine Learning. The second part will focus on producing high-quality data visualization with powerful open source tools such as R. In this part, you'll explore how visualizations, from the static chart to the interactive dashboard, can help you understand your data, deliver insights and impact decision making. Examples will cover diverse types of data, including time series, cartography and networks.

Part 1 – Machine Learning
09:00 Anomaly detection
09:50 Text classification
10:30 Coffee break
11:00 Image classification
11:40 Face recognition
12:30 Lunch break

Part 2 – Data visualisation
13:30 Visualisation 101, time series
15:10 Coffee break
15:20 Visualisation of network and geospatial data
17:10 End of workshop

• Get a first hands-on experience of Machine Learning and Deep Learning
• Understand the potential of Machine Learning and Deep Learning through different use cases
• Attendees will be able to use a set of Shiny Apps from their browser

• Laptop with a recent browser
• Prior programming experience will help but is not expected