Description: The workshop shows how to do big data research using both supervised and unsupervised learning. In the first part, the workshop shows how to use classification and regression models to explain and predict relationships in data with known response variable of interest (i.e., labeled data) and how to find patterns in unlabeled data using clustering and dimensionality reduction. In the second part, the workshop introduces participants to neural networks using Keras library and how to analyze textual data with natural language processing methods (such as principal component analysis, word embeddings). The workshop requires an elementary knowledge of Python and data science which can be acquired in the beginner’s guide workshop.
About the lecturer: Marcel Tkáčik is a doctoral student at the department of management. He teaches a popular course Big data in management. His research interests lie in machine learning applications, natural language processing methods in business and management research. He used to be employed at Deloitte Advisory as a Data Scientist, Applied Economics Consultant.