Weekly Digest for Data Science and AI - Issue #13

One of the hardest tasks after creating your machine learning models is putting them into production. Data engineering takes care of this after the data scientist creates the models, but it's still not an easy process. Deploying machine learning data pipelines and algorithms should not be a time-consuming or difficult task. MLeap allows data scientists and engineers to deploy machine learning pipelines from Spark and Scikit-learn to a portable format and execution engine.