From 2 to 3 May 2023, the Orange workshop for Data Science took place at K1-MET in Linz. The target group comprised all K1-MET employees who deal with the evaluation of data (regardless of their origin).
The workshop included statistical basics and an introduction to the terminology and basics of machine learning. In a hands-on session, the Orange Data Mining Tool (https://orangedatamining.com/) was used to show the possibilities of advanced data analysis and visualization with practical examples.
Goals of the Orange workshop:
- Knowledge of the statistical basics (position and extent of dispersion / distribution analysis / outlier issues) for processing the data
- Knowledge and selection of the appropriate methods for visualizing the data
- Basic knowledge of statistical methods for data analysis (correlation coefficients / linear regression)
- Overview of higher statistical methods / machine learning techniques
- Understand the limitations of applicability and the prerequisites for using the methods
Content of the programme:
- Introduction to Visualization / Machine Learning “Light”
- Introduction to Machine Learning including the importance of “good data” with examples, handling of outliers, existing data sources / databases, the meaning of machine learning and the difference between machine learning, deep learning etc., the limits of technology, pitfalls when setting up such projects and the assessment of the degree of complexity of a potential project (from simple regression to autonomous driving)
- Example projects and discussion of potential projects from the different areas
- Sensor technology / plant data visualization / image processing / big data to show potential for new projects