Anaconda's Python/R Distribution Sets the Stage for Scalable Machine Learning - The New Stack

When it comes to managing the development of machine learning models, git just doesn't get it. This is the lesson learned by Max Humber, a data scientist with the Canadian finance company Wealthsimple, an insight that he shared in a talk at this year's Anaconda annual user conference, AnacondaCon, held in Austin, Texas. "Git manages for code, it is not really great for managing model parameters," he said. Finding the best model, and tuning it accordingly involves a lot trial-and-error. Much of it involves swapping models in and out of the code, then adjusting the parameters.