Artificial intelligence is among the fastest-growing industries. The number of open-source ML libraries to which the best programmers contribute new features and functionalities is constantly increasing.
With fast-paced advances in machine learning, some ML frameworks and libraries become outdated after a certain period of use. In contrast, others gain momentum thanks to the cutting-edge tools they offer to ML engineers.
In this blog post, we present 15 ML libraries to pay attention to in 2023.
What is a machine learning library?
There is a common confusion between libraries and frameworks. So before we move on to introducing the top 15 machine learning libraries and their benefits, let’s explore the key distinction between libraries and frameworks.
Libraries provide specific functionalities, while frameworks offer a complete set of tools for developing a fully-fledged application. So when designing a software solution, you might use many libraries, but typically only one or a few frameworks.
A library is a collection of prewritten codes, predefined methods, and classes that programmers can use to simplify and accelerate development and solve a specific problem. It includes functions, class definitions, important constants…
