machine learning How to ML - Monitoring As much as machine learning developers like to think that once they've got a good enough model, the job is done, it's not quite so. The first couple of weeks
machine learning How to ML - Deploying So the ML engineer presented the model to the business stakeholders and they agreed that it performed well enough on the key metrics in testing that it's time to deploy
machine learning How to ML - Models So we finally got our data and we can get to machine learning. Without the data, there is no machine learning, there is at best human learning, where somebody tries
machine learning How to ML - Data So we've decided what metrics we want to track for our machine learning project. Because ML needs data, we need to get it. In some cases we get lucky and
machine learning How to ML - Metrics We saw that machine learning algorithms process large amounts of data to find patterns. But how exactly do they do that? The first step in a machine learning project is
machine learning What is ML? part 3 Yesterday we saw that machine learning is behind some successful products and it does have the potential to bring many more changes to our life. So what is it? Well,
machine learning What is ML? part 2 Yesterday I wrote how AI made big promises in the past but it failed to deliver, but that now it's different. What's changed? Well, now we have several products that
