Use cases

ONE FRAMEWORK, A LOT OF POSSIBILITIES, YOUR OPPORTUNITIES...

Substra framework is young, but we have already been able to identify and work on several use cases that we present in this section. 

Have you identified new use cases? We would be happy to discuss about them with you. Join our Slack, a section is dedicated to projects to share around your Substra experience.... 

Consortium between competitors

Machine learning algorithms require a large amount of data to increase their performance. But, within an industry, this data is often scattered among different actors who cannot afford to share what is the core of their business. (…)

Collaborations between data providers and data scientists

To develop new algorithms or improve their existing models, data scientists need a large amount of data. But the data is sometimes not accessible to them because it’is too confidential to be shared by the organizations that collected them. Data can also be spread among a large number of different suppliers. (…)

Machine Learning Challenges on sensitive data

Machine learning challenges are a structuring part of the data science landscape. However, they are still limited because of a main obstacle: it is difficult to open your data to external third parties, either because of their value or because they are confidential (....)