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Learning Logs are a personalized learning resource for children. In the learning logs, the children record their responses to learning challenges set by their teachers. Each log is a unique record of the child's thinking and learning. The logs are usually a visually oriented development of earlier established models of learning journals, which ...
e. In mathematics, the logarithm is the inverse function to exponentiation. That means that the logarithm of a number x to the base b is the exponent to which b must be raised to produce x. For example, since 1000 = 103, the logarithm base of 1000 is 3, or log10 (1000) = 3.
Learning pyramid. The learning pyramid (also known as “the cone of learning”, “the learning cone”, “the cone of retention”, “the pyramid of learning”, or “the pyramid of retention”) [1] is a group of popular learning models and representations relating different degrees of retention induced from various type of learning.
Comparison of Linear, Concave, and Convex Functions In original (left) and log10 (right) scales. In science and engineering, a log–log graph or log–log plot is a two-dimensional graph of numerical data that uses logarithmic scales on both the horizontal and vertical axes. Power functions – relationships of the form – appear as straight ...
In computational learning theory, probably approximately correct ( PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant. [1] In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.
Learning Ally, previously named Recording for the Blind & Dyslexic (RFB&D), is a non-profit volunteer organization operating nationwide in the United States.It produces and maintains a library of educational accessible audiobooks for people who cannot effectively read standard print because of visual impairment, dyslexia, or other disabilities.
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Layer types. The first type of layer is the Dense layer, also called the fully-connected layer, and is used for abstract representations of input data. In this layer, neurons connect to every neuron in the preceding layer.
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