by naveen.kumar@openweaver.com Updated: Apr 6, 2022
C++ is an experienced language with a vast history of development. Its long existence and the diversity of its implementations make it a popular choice for many developers. But in the last decade, a new trend has emerged: machine learning. Although it might seem like new technology, its roots stretch back to the late 1950s. And despite its growth exponentially over the last few years, C++ has been used for machine learning applications since the early 2000s. Many developers depend on the following open source libraries: C-Plus-Plus - Collection of various algorithms in mathematics, machine learning, computer science, and physics implemented in C for educational purposes; Flashlight - standalone library for machine learning; Dlib - a toolkit for making real-world machine learning and data analysis applications. Check out the 7 best C++ libraries to use in machine learning projects this year.
C++ 23038 Version:Current
C++ 23038 Version:Current License: Permissive (MIT)
C++ 11682 Version:19.24.0
C++ 11682 Version:19.24.0 License: Permissive (BSL-1.0)
C++ 4710 Version:v0.3.2
C++ 4710 Version:v0.3.2 License: Permissive (MIT)
C++ 4222 Version:4.0.1
C++ 4222 Version:4.0.1 License: Others (Non-SPDX)
C++ 1713 Version:v5.2.122
C++ 1713 Version:v5.2.122 License: Permissive (MIT)
C++ 257 Version:Current
C++ 257 Version:Current License: Permissive (MIT)
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