There are three different methods of streamging: At least once, at most once and exactly once. Listen why it makes a huge difference which one you use. Because not every system or tool supports all three.

Where to get dirty data to train cleaning it?

What are unicorn data scientists and what is THE skill you need if you aren't one.

How to define a data science problem.

NoSQL databases like HBase are awesome!

But why and when should you use them?

How does a key value store like HBase work?

Today I am talking about exactly that

Creating a Gaming-AI with Reinforcement Learning • Creating a Gaming-AI with Reinforcement Learning

Loosing money with data science in the short term does not matter. It's about the long run, not quick sales.

This is a story about how this happened in the insurance industry. And how to go at it to turn this loss into a win

Swish the Swedish Fintech that Blew My Mind in 2017

Chat and Q&A about data science with data scientists

It is very important for me to keep track of emerging technologies and trends. You want to know where the industry is headed. You don't want to miss the next big thing.

This is where Gartner's Hype Cycles help a lot.

Especially the hype cycle for emerging tech.

How to convince people that machine learning actually works? It's simpler than you think.

You have the data. Data doesn't lie!