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Level up your office game, automate your daily tasks, and wow your boss with this comprehensive Excel training course. Excel from Beginner to Advanced is a comprehensive Microsoft Excel course ...
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update the best predictor for future data at each step, as opposed to batch learning techniques which generate the best predictor by learning on the entire training data set at once. Online learning ...
3Blue1Brown started as a personal programming project in early 2015. In an episode of the podcast Showmakers, Sanderson explained that he wanted to practice his coding skills and decided to make a graphics library in Python, which eventually became the open-source project Manim (Mathematical Animation Engine). [17]
The competitive ratio of an online problem is the best competitive ratio achieved by an online algorithm. Intuitively, the competitive ratio of an algorithm gives a measure on the quality of solutions produced by this algorithm, while the competitive ratio of a problem shows the importance of knowing the future for this problem.
Margin-infused relaxed algorithm (MIRA) [1] is a machine learning algorithm, an online algorithm for multiclass classification problems. It is designed to learn a set of parameters (vector or matrix) by processing all the given training examples one-by-one and updating the parameters according to each training example, so that the current training example is classified correctly with a margin ...
The List Update or the List Access problem is a simple model used in the study of competitive analysis of online algorithms.Given a set of items in a list where the cost of accessing an item is proportional to its distance from the head of the list, e.g. a linked List, and a request sequence of accesses, the problem is to come up with a strategy of reordering the list so that the total cost of ...
Co-training is a machine learning algorithm used when there are only small amounts of labeled data and large amounts of unlabeled data. One of its uses is in text mining for search engines . It was introduced by Avrim Blum and Tom Mitchell in 1998.
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