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Simulation uses models constructed by experts to predict probabilities. Machine Learning builds its own models to predict future outcomes. Monte Carlo (the place) is the iconic capital of gambling—an endeavor that relies exclusively on chance probabilities to determine winners and

Data Mining describes patterns, correlations, and anomalies in data. Mines are not the best analogies for the processes referred to as Data Mining. Never mind that we call data storage places bases, warehouses, and lakes. Extraction of raw data material is not

Deep Learning is a category of machine learning with special advantages for some tasks and disadvantages for others. Machine learning workflows begin by identifying features within data sets. For structured information with relatively few columns and rows, this is straightforward.

Classifications are the most frequently used—and most useful—prediction types. Classifications are predictions that separate data into groups. Binary Classification produces “yes-no” or “in-out” answers when there are only two choices. Multi-Class Classification applies when there are three or more possibilities and shows probabilities

Predictions are interesting on their own. They are valuable when put into production. Operationalizing AutoML – often called “ML Ops” – means putting AutoML predictions into regular workflows to change business outcomes. Here are a few ways do it. Graphical