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An Hour of code tutorial: Hour of code is a worldwide initiative to engage students in computer science, by providing 60 minute-long ludic introduction tutorials (for instance with Minecraft or frozen components). [7] This particular tutorial is an introduction to computer science where students compose their first song with EarSketch.
RapidMiner: Formerly Yet Another Learning Environment (YALE): free open-source software for knowledge discovery, data mining, and machine learning also featuring data stream mining, learning time-varying concepts, and tracking drifting concept. It is used in combination with its data stream mining plugin (formerly concept drift plugin).
In the synthetic track, methods were compared according to five properties: re-discovery of exact expressions; feature selection; resistance to local optima; extrapolation; and sensitivity to noise. Rankings of the methods were: QLattice; PySR (Python Symbolic Regression) uDSR (Deep Symbolic Optimization)
Python's name is derived from the British comedy group Monty Python, whom Python creator Guido van Rossum enjoyed while developing the language. Monty Python references appear frequently in Python code and culture; [190] for example, the metasyntactic variables often used in Python literature are spam and eggs instead of the traditional foo and ...
An illustration of fluid simulation using VOF method. In computational fluid dynamics, the volume of fluid (VOF) method is a family of free-surface modelling techniques, i.e. numerical techniques for tracking and locating the free surface (or fluid–fluid interface).
For example, in statistical parsing a dynamic programming algorithm can be used to discover the single most likely context-free derivation (parse) of a string, which is commonly called the "Viterbi parse". [4] [5] [6] Another application is in target tracking, where the track is computed that assigns a maximum likelihood to a sequence of ...
Filter feature selection is a specific case of a more general paradigm called structure learning.Feature selection finds the relevant feature set for a specific target variable whereas structure learning finds the relationships between all the variables, usually by expressing these relationships as a graph.
Every output random variable from the simulation is associated with a variance which limits the precision of the simulation results. In order to make a simulation statistically efficient, i.e., to obtain a greater precision and smaller confidence intervals for the output random variable of interest, variance reduction techniques can be used ...