Engineering Machine Learning Pipelines using DaskML

Machine learning is a branch of artificial intelligence and computer science. A machine learning model is an intelligent system that can learn from data in order to make decisions. Organizations of all nature have gained significant value by leveraging machine learning models in their processes. Training a machine learning model is done using algorithms, which can be computationally expensive. As datasets grow larger, both in terms of volume and level of complexity of the data points, scalable machine learning solutions are highly sought after. In this chapter we will look at Dask-ML, a library that runs ML algorithms in a distributed computing environment and integrates well with existing modern data science libraries.