Wiki Culture Meets Machine Learning

Wiki Way Machine Learning – Where Wiki Culture Meets Machine Learning

Wiki Way Machine Learning program frames machine learning by managing projects that combine the best of a pragmatic wiki culture and project model with the latest Open Source Machine Learning tooling (i.e., Rubix ML) to produce outcomes for our clients.

It’s not enough to have machine learning tools. If you want to get projects delivered in a way that produces the best outcomes, you will need to combine this technology with people, process, and data. Wiki Way Machine Learning, we would argue, is a great way to do that. To learn more about the Wiki Way, and how it can benefit your machine learning project, reach out to us. We’re happy to share our experiences.

I’m looking to learn machine learning

If you’re looking to learn how to use Machine Learning, then the best way to start is to first understand the basic principles of the discipline, to then progress into applying simple algorithms to problems. The Rubix ML site has everything you need to get started on your Open Source Machine Learning journey. Also, spare a thought for other complementary Open Source projects like WikiSuite and Tiki. There are great tools like Tiki Trackers you can use in your projects to capture, manage and share data.

One of the great things about using Open Source is that you’ll find there are lots of willing people on hand to help you achieve your goals. Everyone in the Open Source community joins in to share ideas and support others in their learning journeys. While it requires a high level of dedication to come to grips with Machine Learning (yep, there’s lots to learn) when you’re part of the Open Source community, you will never be on your own. To take your first step, visit the Rubic ML Get Started page.