The praktikum allows students to gain practical knowledge and capabilities in the area of Machine Learning. Praktikum will also cover empirical methods for comparing learning algorithms, for understanding and explaining their differences, for analyzing the conditions in which a method is more suitable than others

On weekly or bi-weekly basis, we will cover

• Multicore and Multi-Threaded programming for share memory systems
• Message Passing Interface (MPI)
• Hadoop Framework and MapReduce programming model
• Large Scale distributed file systems and data storage frameworks
• Apache Spark and NoSQL databases
• Graphlab and cassandra databases
• Implement distributed algorithms i.e. ADMM, PSGD etc
• Introduction to cloud services i.e. Amazon EC2, Microsoft azure and ISMLL Cluster

• Tutorials will be held every week
• An implementation assignment will be given every week
• A solution to the assignments is discussed in the next lab session
• The final grade of praktikum depends on the points in each submitted assignment

Registration:

• You can register for Praktikum through LSF
• For further details please contact Daniela Thyssens