When you choose a machine learning tool, you choose your future. We all know how quickly everything changes in the world of artificial intelligence, so it is important to keep the balance between “old dog, old tricks” and “just made it yesterday”.

In this post, we are going to have a look at 18 popular machine learning tools. This review will cover ML platforms, frameworks, and ML libraries.

Top machine learning frameworks, libraries and platforms

First, we are going to talk about platforms. They are built on a single channel architecture and designed in a way that it is convenient to program tasks. They may offer other services like work in the cloud, collaborative working options, or graphic processors for data visualization. They also use popular frameworks by Google, Microsoft, or Amazon.

Then, we will have a look at the frameworks to use when developing an ML application.

Machine learning platforms

If you are starting to work with ML, a platform with ready-made datasets and standard model templates will allow you to create your first solutions quicker and with fewer bugs. These platforms install all the necessary tools to let you start working in no time.

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