Closed KanizoRGB closed 3 years ago
seems like a helpful topic - lets please be sure it add value beyond what is in the official docs and that it does not overlap with any existing EngEd articles or incoming topic suggestions (if you haven't already). - approved @KanizoRGB
@KanizoRGB Just wanted to follow up on this topic, as we will be clearing up the queue where possible.
@paulodhiambo are you the reviewer?
merged
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Proposed title of article
Machine learning libraries in C++
Introduction paragraph (2-3 paragraphs):
What is the essence of using libraries for machine learning? This is a sequel to an earlier article where we implemented algorithms from scratch. Libraries enable the reuse of code for solving problems. The code could have been implemented by an expert or an enthusiast. This saves one from the problem of having to "reinvent the wheel" each time especially when working or learning under strict deadlines. C++ as a programming language has libraries that are useful for machine learning. In this article, we will look at the SHARK and MLPACK libraries and exploit their functionality in machine learning.
Key takeaways:
1.The reader will learn how to install libraries and set up the environment on their computers. 2.The reader will learn how to use libraries to implement common machine learning models. 3.The reader will also get the gist of libraries and their use in solving common repetitive problems and not just for machine learning.
References:
1.https://www.mlpack.org/doc/mlpack-3.2.2/doxygen/build.html 2.http://www.shark-ml.org/sphinx_pages/build/html/rest_sources/tutorials/tutorials.html 3.https://www.analyticsvidhya.com/blog/2019/08/comprehensive-guide-k-means-clustering/?utm_source=blog&utm_medium=introduction-machine-learning-libraries-c
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