In this lecture, we focus on predictive modeling (machine learning) via Python and how to solve the related business problem.
Programming skills are mandatory for a data scientist; thus, programming exercises have to be done by the students. Predictive models forecast the future given historical data sets. For this machine learning might become appropriate. We will use the scikit-learn Python library and TensorFlow to demonstrate pitfalls and best practices to solve a problem. Also, the link to advanced business intelligence (BI) tools and in-memory databases is presented.
Note that full coverage of these topics is not possible, and only a selective view is presented. Thus, only basic concepts are sketched by using demos, SQL, Python, and business process modeling and notation (BPMN) representation.