machine learning
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 establishing metrics. What exactly do we want to do and how do we know we're doing it well?
machine learning
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, the textbook definition is that it's the building of algorithms that can perform tasks they were not explicitly
machine learning
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 work well with machine learning. My favorite example is Google Photos, Synology Moments and PhotoPrism. They
machine learning
Machine learning is everywhere these days. Mostly in newspapers, but it's seeping into many real life, actual use cases. But what is it actually? If you read only articles on TechCrunch, Forbes, Business Insider or even MIT Technology Review, you'd think it's something that