Discover the concepts of pushdown automata, Turing machines, and finite transducers in this 12-video course, in which learners can examine how to identify limitations and complexities in computation and how to apply P and NP classes to manage them. Begin by recalling the machine learning analytical capabilities of grammar, then look at context-free grammar normal forms, using Chomsky normal forms and Greibach normal forms to manage context-free grammars. Describe pushdown automata and features of nondeterministic pushdown automata. This leads on to Turing machines, their capabilities, and the prominent variations in the building themes of Turing machines. Learners explore the concept of finite transducers, and the types of finite transducers. Recall the underlying limitations of computations and the limitations of computational theory, and the complexities of computation, computational theory complexities, and how it can impact Turing machine models and language families. Learn about handling computation complexities with P class and handling computation complexities with NP class. The concluding exercise involves describing properties and variations of Turing machines, types of finite transducers, and properties of recursively enumerable languages.
Computational Theory: Using Turing, Transducers, & Complexity Classes