Machine learning is often split between three main types of learning: supervised learning, unsupervised learning, and reinforcement learning. Knowing the differences between these three types of learning is necessary for any data scientist. The big picture The type of learning is defined by the problem you want to solve and ...

Hyperparameter tuning with mlr is rich in options as they are multiple tuning methods: Simple Random Search Grid Search Iterated F-Racing (via irace) Sequential Model-Based Optimization (via mlrMBO) Also the search space is easily definable and customizable for each of the 60+ learners of mlr using the ParamSets from the ParamHelpers ...

Hyperparameter tuning with mlr is rich in options as they are multiple tuning methods: Simple Random Search Grid Search Iterated F-Racing (via irace) Sequential Model-Based Optimization (via mlrMBO) Also the search space is easily definable and customizable for each of the 60+ learners of mlr using the ParamSets from the ParamHelpers ...

Blue dragonflies dart to and fro I tie my life to your balloon and let it go (Warm Foothills, Alt-J) In my last post I did some drawings based on L-Systems. These drawings are done sequentially. At any step, the state of the drawing can be described by the position (...

Here is a course with videos that present Multiple Correspondence Analysis in a French way. The most well-known use of Multiple Correspondence Analysis is: surveys. Four videos present a course on MCA, highlighting the way to interpret the data. Then  you will find videos presenting the way to implement MCA ...