AI & Machine Learning
Use the right tool for the right problem
The ongoing AI revolution has given us many different algorithms, programming languages and frameworks for problem solving using data. Which should we use for what? Should you use R, Python or Scala? Linear Regression, a Gradient Boosting Machine, or a Convolutional Neural Network? Do you need to use Spark? Let’s clarify which solution will work best for you.
It doesn’t have to be complicated
On the contrary, a simple model works many times better than a complicated one. Of course, a complicated model can find contexts that a simple model cannot find. On the other hand, there is a risk of finding relationships that do not really exist. To succeed with AI, an understanding of what works, as well as an understanding of what can go wrong, is required.