Managers have a key role to play to make Machine Learning (ML) work for any organization. This non-technical but practical workshop is the first to be designed for Managers with no prior knowledge of ML. It provides the missing piece to identify the best opportunities with Machine and Deep Learning (DL) technologies, to apply them in your own projects, and to generate business value from data.
This workshop is focused not on teaching algorithms, but on how to make them work in the real world, and on key knowledge to start managing ML projects effectively. It will bring you up to speed on core ML concepts, illustrated with example use cases. It will also provide you with hands-on experience of the main steps in a typical ML workflow, by using point-and-click tools to compete in a Data Science challenge (Dataiku for easy data preparation, BigML for automated ML/DL, and Google Sheets). You will learn how to set up and structure a successful ML project, and how to set direction for your team's work, with the help of the Machine Learning Canvas.
If you are a Manager, you will save months of work for your whole team by understanding the principles taught in this workshop. If you are a Developer or a Scientist, this is the workshop to recommend to your Manager, to better understand what today’s ML techniques can/cannot do.
BONUS — Free book for all participants: Bootstrapping Machine Learning
- Understand the unique opportunities ML creates, and its limitations.
- Learn how to use the ML Canvas to frame ML problems, design real-world ML systems, and set up your own ML projects.
- Gain a practical understanding of the steps in a typical ML workflow. Learn about the various components of an ML platform.
- Design domain-specific evaluation procedures and performance metrics. Understand how a poor evaluation procedure can wildly overestimate performance in production.
Technical managers and decision-makers
Registration & practical information
This workshop will be held as part of the PAPIs Latam 2019 conference, on 24 June 2019 in São Paulo, Brazil. Registration will open soon at https://www.papis.io/latam-2019.