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Jupyter Notebooks can execute cells of Python code, retaining the context between the execution of cells, which usually facilitates interactive data exploration. [5] Elixir is a high-level functional programming language based on the Erlang VM. Its machine-learning ecosystem includes Nx for computing on CPUs and GPUs, Bumblebee and Axon for ...
Question-answer pairs Question Answering 2020 [334] Nguyen et al. Vietnamese Multiple-Choice Machine Reading Comprehension Corpus(ViMMRC) A collection of Vietnamese multiple-choice questions for evaluating MRC models. This corpus includes 2,783 Vietnamese multiple-choice questions. 2,783 Question-answer pairs
Multiple choice questions lend themselves to the development of objective assessment items, but without author training, questions can be subjective in nature. Because this style of test does not require a teacher to interpret answers, test-takers are graded purely on their selections, creating a lower likelihood of teacher bias in the results. [8]
PCFGs models extend context-free grammars the same way as hidden Markov models extend regular grammars.. The Inside-Outside algorithm is an analogue of the Forward-Backward algorithm.
The outcome after 6 rounds, during which participants swap their worksheets passing them on to the team member sitting at their right, is 108 ideas generated in 30 minutes. The technique is applied in various sectors but mainly in business , marketing , design , and writing , as well as everyday real life situations.
(In Python, Ruby, PARI/GP and other popular languages, A & B == C is interpreted as (A & B) == C.) Source-to-source compilers that compile to multiple languages need to explicitly deal with the issue of different order of operations across languages. Haxe for example standardizes the order and enforces it by inserting brackets where it is ...
Processes related to functional decomposition are prevalent throughout the fields of knowledge representation and machine learning.Hierarchical model induction techniques such as Logic circuit minimization, decision trees, grammatical inference, hierarchical clustering, and quadtree decomposition are all examples of function decomposition.
In artificial intelligence, symbolic artificial intelligence (also known as classical artificial intelligence or logic-based artificial intelligence) [1] [2] is the term for the collection of all methods in artificial intelligence research that are based on high-level symbolic (human-readable) representations of problems, logic and search. [3]