Studies

193
Compulsory

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Description

This course will provide students with an introduction to Data mining and Statistical pattern recognition techniques in order to make sense of data at scale. The course material will not only provide the theoretical background of the techniques involved, but engage you to gain the practical knowledge of prototyping these solutions on problems yourself in Python.

Some of the topics covered will be: Visualisation Machine learning basics: Regression, k-Nearest Neighbours and k-Means Classification Bayesian Methods Tree-based methods Support Vector Machines Unsupervised learning and Deep learning Visual Recognition Machine learning at scale with Spark and MlLib

Cross-language

193 029
Compulsory

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AncillaryCourses

Übung zu Data Science: Statistical Learning and Data Mining

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