Datadive.net Website Review

In practical machine learning and data science tasks, an ML model is often used to quantify a global, semantically meaningful relationship between two or more values. For example, a hotel chain might want to use ML to optimize their pricing … Continue reading → In two of my previous blog posts, I explained how the black box of a random forest can be opened up by tracking decision paths along the trees and computing feature contributions. This way, any prediction can be decomposed into … Continue reading → The need for anomaly and change detection will pop up in almost any data driven system or quality monitoring application. Typically, there a set of metrics that need to be monitored and an alert raised if the values deviate from … Continue reading → Like with any sport, the question of who are the best competitors of all time in Mixed Martial Arts (MMA) is something that is hotly debated among MMA fans. And unlike for tournament based sports such as tennis, or sports … Continue reading → Today, we had the first event of the Estonian Machine Learning Meetup series. I was quite baffled by the pretty mas*ive turnout, with more than a hundred people attending, indicating that such an event series is long overdue. So props … Continue reading → There is huge number of machine learning methods, statistical tools and data mining techniques available for a given data related task, from self organizing maps to Q-learning, from streaming graph algorithms to gradient boosted trees. Many of these methods, while … In one of my previous posts I discussed how random forests can be turned into a “white box”, such that each prediction is decomposed into a sum of contributions from each feature i.e. .I’ve a had quite a few requests … Continue reading → An aspect that is important but often overlooked in applied machine learning is intervals for predictions, be it confidence or prediction intervals. For clas*ification tasks, beginning practitioners quite often conflate probability with confidence: probability of 0.5 is