Marcel Tilly & Olivia Klose – My Robot can learn – using Reinforcement Learning to teach my Robot

Abstract: My Robot can learn – using Reinforcement Learning to teach my Robot A new star is rising at the machine learning horizon: reinforcement learning (RL). The concept entails an agent and an incentive-based training system. The agent learns via incentives and improves its behaviour – a self-learning system using simple rules – leading to[…]

Markus Ziller – From Pokémon to Donald Trump – Mining and Visualizing weird stuff

Abstract: From Pokémon to Donald Trump – Mining and Visualizing weird stuff In his talk, Markus talks about extracting, analyzing and visualizing data from unusual sources. He will talk about two of his projects: First he’ll talk about using a Pokémon Go bot to gather and processing data on 250k spawns of Pokémon in Munich[…]

Alexander Hirner – Transfer Learning for Fun and Profit

Abstract: Transfer Learning for Fun and Profit Transfer learning is exciting because it unlocks solutions that weren’t feasible a few years ago. In fact, choices to compose from pre-trained models for computer vision tasks became abundant. In this talk, we will explore how to make these choices for image classification and feature extraction. The analysis is[…]

Daniel Kühn – Make hyperparameters great again

Abstract: Make hyperparameters great again While tuning hyperparameters of machine learning algorithms is computationally expensive, it also proves vital for improving their predictive performance. Methods for tuning range from manual search to more complex procedures like Bayesian optimization. This talk will demonstrate the latest methods for finding good hyperparameter-sets within a set period of time for[…]

Heeren Sharma – Content-As-A-Service

This talk is centered around building real-time and lightening responsive news search engine. From streaming data processing to system architecture, all bits and pieces will be covered. Specially in case of news articles streaming in the system, challenges and whole ecosystems of aggregation to scoring algorithm will be introduced. Realisation of plug and play micro-service[…]

Fabian Dill – Word Embeddings – the Good, the Bad, and the Ugly

Abstract: Word Embeddings – the Good, the Bad, and the Ugly Word embeddings are the new magic tool for natural language processing. Without cumbersome preprocessing and feature design they are able to capture the semantics of language and texts, simply by being fed with lots of data. So they say. We applied word embeddings –[…]