Session type:

Case Study

Presented by:

Ritika Singh

Underwriteme

Session time:

30 Jun 13:45 14:30

Session duration:

45 minutes

About the session

We have come a long way in the world of machine learning with complex models being built capable of doing a lot of great things. 

The systems that can make these possible are complex by nature, and so are the teams that build them; typically composed of data engineers, data scientists and IT engineers.

The projects in the field of machine learning and artificial intelligence are complex and often experimental by nature, making agile practices difficult to be implemented.

In this session we will go through an experience of implementing agile practices in the machine learning field.

Participant Takeaways:

  • Agile implementation in machine learning industry
  • Metrics which can help researchers/data scientists in an agile environment
  • Frameworks that can work well with software engineers, researchers, and data scientists.

Themes:
Agile Transformation, Agile in Machine Learning, Agile Metrics, Agile Culture, Agile Mindset

About the speaker(s)