Dennis Gluesenkamp's repositories
violence-against-women
Violence against women, especially in intimate relationships, is a global scourge that does not halt at any cultural or social group. According to Oxfam, one in three women in the world experiences some form of violence in the course of their lives and thus a profound violation of their human rights. On this subject, the OECD's open database contains a source of figures from many countries around the world. Although the figures given there are from 2014, the problem is persistent and still of acute importance. It is therefore a central concern of this work to recall the figures and to raise awareness of the problem. For this reason, two indicators from this data source are considered and presented as visualizations in the following.
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.
dgluesen.github.io
Portfolio
relevance-nfl-statistics
Nowadays, sports events live above all from their media coverage, which includes cheering up winners and writing down losers. Statitstics are used to underpin the own argumentation in this reports. But is there any cherry picking here? Are only those statistics used that make the report/commentary look completely logical? In order to give an initial assessment of the relevance of typically used statistics of NFL games, a simple but easily understandable machine learning approach is presented. This reveal statistics which might be used as a solid basis for argumentation.
ss20-applied-programming
This repository contains the scripts and notebooks for my lecture "Applied Programming" at FOM in summer term 2020.
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.
ab-testing-trials
Development of the theoretical basis for statistical hypothesis testing with calculation of sample data sets
cheat-sheets
Collection of self created cheat sheets on different topics.
data-strategy
An approach to the agile desing and implementation of a data strategy in businesses