Lecture
This lecture presents an internship experience at Nestlé by a digital humanities master student from EPFL. The student discusses their six-month internship, focusing on two main projects that utilized machine learning. The first project aimed at predictive maintenance for coffee machines, addressing the challenges of high maintenance costs and customer satisfaction. The student explains how they conducted a literature review to select appropriate machine learning algorithms and developed a data pipeline for predictive analysis. This approach successfully reduced downtime and maintenance costs while enhancing customer satisfaction. The second project involved understanding customer churn through machine learning explainability, aiming to uncover reasons behind customer departures and provide actionable insights for retention strategies. The student highlights the importance of model interpretability to ensure stakeholders can understand the insights generated. Overall, the internship provided valuable experience in applying data science skills and fostering teamwork within a supportive environment.