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 →

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 … Continue reading →