In just the last few years, Machine Learning has gone from something barely known outside of academic circles, to becoming now a critically important tool for optimizing business operations. Assuming an organization even has a small team of ML experts, as the number of ML applications explodes, the pressure on these teams and their hand tailored solutions brings innovation to a halt.
As a result, many organizations are beginning to realize that the solution is to bring ML to everyone as a standardized platform. So, what should you be looking for in a platform? As easy as it it to make a wishlist of features, it's equally easy to overlook the importance of automation. ML tasks are iterative by nature and automation of the tasks and workflows is essential. In this talk you will see how WhizzML is making automation easy, reducing the need for experts, and putting the Machines back into Machine Learning.
Poul is Chief Infrastructure Officer at BigML. He has an MS degree in Mathematics as well as BS degrees in Mathematics, Physics and Engineering Physics. With 20 plus years of experience building scalable and fault tolerant systems in data centers, Poul currently enjoys the benefits of programmatic infrastructure, hacking in python to run BigML with only a laptop and a cloud.