Dennis Gluesenkamp's starred repositories
skope-rules
machine learning with logical rules in Python
wrangling-sales-workload
Raw data of real analytical use cases in a number of industries and companies are frequently provided in an Excel-based form. These files usually cannot be processed directly in machine learning models, but must first be cleaned and preprocessed. In this process, many different types of pitfalls may occur. This makes data preprocessing an essential time factor in the daily work of a data scientist. In this concise project an Excel spreadsheet will be presented which in this form is closely oriented to a real case, but contains only simulated figures for reasons of data and business results protection. However, the form and structure of the file corresponds to a real case and could be encountered by a data scientist in a company in this way.
datascience-career-crisp-dm
How can I share my own professional experience with Master's students in business analytics and data science? Encourage them to self-reflect? I asked myself this question recently when I was invited to give a guest lecture at a university of applied sciences. My approach is to adapt the CRISP-DM process model which is familiar to many students and practitioners in the field of data science.