SoSe 15: Data Science: Statistical Learning and Data Mining
Kashif Rasul
Additional information / Pre-requisites
We will provide extra tutorials to students not familiar with the Mathematical and Statistical background needed. The lecture will be held in English.
Kindly make sure you have an updated python development setup with iPython, Scipy, Numpy, Pandas and Scikit-learn installed. We recommend using the Anaconda distribution. You will need a Github account as well as a Kaggle account so make sure you are signed up before class begins.
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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
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Additional appointments
Fri, 2015-04-17 10:00 - 12:00 Fri, 2015-04-24 10:00 - 12:00Regular appointments
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 ... read more