A Tour of Machine Learning Algorithms

Originally published by Jason Brownlee in 2013, it still is a goldmine for all machine learning professionals. The algorithms are broken down in several categories. Here we provide a high-level summary, a much longer and detailed version can be found here. Below is a much smaller version. I would add HDT, Jackknife regression, density estimation, attribution modeling (to optimize marketing mix), linkage (in fraud detection), indexation (to create taxonomies or for clustering large data sets consisting of text), bucketisation, and time series algorithms.