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v. t. e. Machine language monitor in a W65C816S single-board computer, displaying code disassembly, as well as processor register and memory dumps. In computer programming, machine code is computer code consisting of machine language instructions, which are used to control a computer's central processing unit (CPU).
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. Recently, artificial neural networks have been able to surpass many previous approaches in performance.
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...
In computer programming, assembly language (alternatively assembler language or symbolic machine code), often referred to simply as assembly and commonly abbreviated as ASM or asm, is any low-level programming language with a very strong correspondence between the instructions in the language and the architecture's machine code instructions.
Low-level programming language. A low-level programming language is a programming language that provides little or no abstraction from a computer's instruction set architecture —commands or functions in the language map that are structurally similar to processor's instructions. Generally, this refers to either machine code or assembly language.
Meta learning is a subfield of machine learning where automatic learning algorithms are applied to metadata about machine learning experiments. As of 2017, the term had not found a standard interpretation, however the main goal is to use such metadata to understand how automatic learning can become flexible in solving learning problems, hence to improve the performance of existing learning ...
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