MLBlocks is a simple framework for seamlessly combining any possible set of Machine Learning tools developed in Python, whether they are custom developments or belong to third party libraries, and build Pipelines out of them that can be fitted and then used to make predictions. This is achieved by providing a simple and intuitive annotation language that allows the user to specify how to integrate with each tool, here called primitives, in order to provide a common uniform interface to each one of them.

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