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Top 5 Libraries in C/C++ for ML in 2023

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As of my last knowledge update in September 2021, I can provide you with a list of popular libraries in C/C++ for machine learning. However, please note that the landscape of machine learning libraries is constantly evolving, and new libraries may have emerged since then. Here are five libraries that were relevant in 2021, and you may want to check if there have been any updates or new additions in 2023:

1. TensorFlow: TensorFlow is a widely used open-source machine learning framework developed by Google. While its primary interface is in Python, it provides a C++ API that allows for efficient inference and integration into C++ applications.

2. PyTorch C++ API: PyTorch, another popular deep learning framework, offers a C++ API that allows developers to use PyTorch models in C++ applications. This API provides similar capabilities to the Python version of PyTorch.

3. MLpack: MLpack is a C++ machine learning library designed for efficiency and ease of use. It provides a wide range of machine learning algorithms, making it suitable for various tasks, including classification, regression, and clustering.

4. Dlib: Dlib is a C++ toolkit for machine learning and computer vision. It includes a variety of machine learning algorithms, as well as tools for image analysis and face recognition. It’s known for its simplicity and efficiency.

5. Shogun: Shogun is a versatile machine learning library that supports multiple programming languages, including C++. It provides a wide range of machine learning algorithms, including support for classification, regression, clustering, and more.

Please check the official websites and repositories of these libraries for the most up-to-date information and compatibility with the latest ML technologies in 2023. Additionally, consider exploring newer libraries and frameworks that may have emerged since my last update, as the field of machine learning is continually evolving.

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