06-07, 15:30–16:15 (Europe/London), Doddington Forum
In data science experimentation is vital, the more we can experiment, the more we can learn.
However quick iteration isn't sufficient we also need to be able to easily promote these experiments to production to deliver value. This requires all the stability and reliability of any production system.
John will discuss building platforms that treat iteration as a first class consideration, the role of open source libraries, and balancing trade-offs.
Previous knowledge expected
John is an Independent Machine Learning & AI Product Consultant based in Manchester. He helps organisations get past the hype and deliver valuable data, and AI products.
John is also chair of the PyData London conference, and an organiser at PyDataMCR