Computational complexity theory

Computation tree

A computation tree is a representation for the computation steps of a non-deterministic Turing machine on a specified input. A computation tree is a rooted tree of nodes and edges. Each node in the tree represents a single computational state, while each edge represents a transition to the next possible computation. The number of nodes of the tree is the size of the tree and the length of the path from the root to a given node is the depth of the node. The largest depth of an output node is the depth of the tree. The leaves of the tree are called output nodes. In a computation tree for a decision problem, each output node is labeled Yes or No. If a tree, T, with an input space X, if and the path for x ends in node labeled yes, then the input x is accepted. Else it is rejected. The depth of the computation tree for a given input is the computation time for the Turing machine on that input. Computation trees have also been used to study the computational complexity of problems in computational geometry and real number calculations. (Wikipedia).

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From playlist The Julia Computer Language

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From playlist Additional Topics: Generating Functions and Intro to Number Theory (Discrete Math)

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From playlist Pre-Calculus / Trigonometry

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From playlist Applied Calculus

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From playlist Introduction to Exponential Functions

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From playlist How to Graph Exponential Functions | Learn About

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From playlist How to Graph Exponential Functions with Stretch and Compression

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From playlist Algorithms

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From playlist Behind the Scenes in Real-Life Software Design

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Anthea Monod (2/11/21): Tropical geometry of phylogenetic tree spaces

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Applied ML 2020 - 08 - Gradient Boosting

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From playlist Applied Machine Learning 2020

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Tree (graph theory) | Real number | Decision problem | Computational geometry