Welcome to The Elements of Data Science. In this course, we join Blaine Sundrud for discussions on how to build and continuously improve machine learning models. Topics include the following elements of data science: problem formulation, exploratory data analysis, feature engineering, model training, tuning and debugging, as well as model evaluation and productionizing.
We’ll explore the machine learning process from end-to-end. It’s important to know how data influences and impacts this process, because your machine learning solution is only as good as the data that drives it.