Search Results for "reasoning machine learning"

A C++ high-performance regex library and Flex-compatible lexical analyzer generator with full Unicode support, new indentation anchors, lazy quantifiers, and many other modern features. Accepts Flex lexer specification syntax and is compatible with Bison/Yacc parsers. Generates reusable source code that is easy to understand. Supports fast scanning of UTF-8/16/32 files, strings, and streams. The reflex scanner generator generates clean C++ lexer class code that is thread-safe. Generates...

...Whether you call it IntelliSense, intelliCode, autocomplete, AI-assisted code completion, AI-powered code completion, AI copilot, AI code snippets, code suggestion, code prediction, code hinting, or content assist, you probably already know that it can save you tons of time, easily cutting your keystrokes in half. Powered by sophisticated machine learning models trained on billions of lines of trusted open source code from GitHub, Tabnine is the most advanced AI-powered code completion copilot available today. And like GitHub, it is an essential tool for professional developers.

pyIRDG is a program written in Python to generate relational datasets in Prolog format. It uses data from the Internet Movie Database in combination with IMDbPY as backend. A graphical user interface written in pyQt allows the user to link multiple entities together as model for the generation process. The big four entities are Title, Person, Company and Character. Many attributes can be chosen for adding to the output .pl file. Three types of constraints on attributes are available to limit...

Hippal is an integrating GUI-framework for a multimodular symbolic A.I.-system IPAL, which combines A.I. Planning, Inductive Program Synthesis, Analogical Reasoning and Learning. Hippal is client-/server-based and uses the Lili Lisp Interpreter as Centr

News: since 2015 we continue all related developments within Collective Knowledge Framework: http://github.com/ctuning/ck/wiki Alchemist plugin is a collection of plugins for GCC/LLVM for external and fine-grain code analysis and tuning. It is intended to to extract program properties for machine learning based optimization (see MILEPOST GCC); optimize programs at fine-grain level (such as unrolling, tiling, prefetching, etc); tune default optimization heuristic; gradually decompose program and detect performance or other anomalies; generate benchmarks particularly useful to train ML-based compilers. GCC plugin is licenced under GPLv3 licensed, while future LLVM plugins will be licensed under BSD license. ...