Property:Prerequisites
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some capability to work with software, and interest in robots and recognition +
A
A Meta-Learning Approach for Preserving and Transferring Beneficial Behaviors in Asynchronous Multi-Agent Reinforcement Learning +
Deep learning course. Good programming knowledge in Python. Good knowledge of ML and preferably Meta-learning/RL and OpenAI gym. +
Good knowledge of applied mathematics and signal processing. An ability to implement state-of-the-art algorithms in a suitable programming environment. An interest in machine learning algorithms. +
Experience with programming, electronics, NFC/Mifare and other wireless protocols and
sensor wearables. Interest and experience in Biohacking and wetware is also good. +
AI, Learning Systems, good programming skills +
Artificial Intelligence, Learning Systems Course +
Machine learning courses +
Good knowledge of machine learning +
Sensor System (7.5 credits), Learning Systems (7.5 credits), Cooperating Intelligent Systems (7.5 credits), or similar +
Solid mathematical and programming skills +
Deep Reinforcement Learning course. Good knowledge of Machine Learning and preferably Reinforcement learning. Good programming skills - Required for the implementation of investigated methods. +
Image analysis, programming skills (preferably C++ or Python) +
Programming skills (preferably C++ or Python) +
Cooperating Intelligent Systems and Learning Systems courses +
Machine Learning, Python +
Artificial Intelligence, Learning Systems, Data Mining +
Data Mining Course +
Python, Deep Learning course, Image Analysis course +
Background in signal analysis and programming are required. Interest in inertial sensors is a bonus. +
