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Artificial Intelligence (Hochschule Ravensburg-Weingarten Univ.). Instructor: Professor Wolfgang Ertel.
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English
English [CC]
FREE
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Description
This course provides an overview of the field of Artificial Intelligence (AI) with its current widespread ramifications. Topics covered in this course include: search, game playing, problem solving; reasoning with Bayesian networks; machine learning and data mining; neural networks; reinforcement learning. And some of the topics will be dealt with in more detail.
Course content
- Lecture 01 – Introduction Unlimited
- Lecture 02 – Search, Games and Problem Solving Introduction Unlimited
- Lecture 03 – Uninformed Search: Breadth-First Search, Depth-First Search Unlimited
- Lecture 04 – Heuristic Search: Greedy Search, A*-Search, IDA*-Search Unlimited
- Lecture 05 – Games with Opponents, Heuristic Evaluation Functions Unlimited
- Lecture 06 – Computing with Probabilities, The Principle of Maximum Entropy Unlimited
- Lecture 07 – The Maximum Entropy Method Unlimited
- Lecture 08 – The Maximum Entropy Method, LEXMED Unlimited
- Lecture 09 – LEXMED, Reasoning with Bayesian Networks Unlimited
- Lecture 10 – Reasoning with Bayesian Networks Unlimited
- Lecture 11 – Reasoning with Bayesian Networks, Machine Learning and Data Mining Unlimited
- Lecture 12 – The Perceptron, The Nearest Neighbour Method Unlimited
- Lecture 13 – The Nearest Neighbour Method, Decision Tree Learning Unlimited
- Lecture 14 – Decision Tree Learning Unlimited
- Lecture 15 – Decision Tree Learning, Learning of Bayesian Networks Unlimited
- Lecture 16 – The Naive Bayes Classifier, Clustering Unlimited
- Lecture 17 – Clustering, Data Mining in Practice Unlimited
- Lecture 18 – Neural Networks: Modeling Learning, Hopfield Networks, Autoassociative Memory Unlimited
- Lecture 19 – Neural Networks: Autoassociative Memory Unlimited
- Lecture 20 – Linear Networks with Minimal Errors, The Backpropagation Algorithm Unlimited
- Lecture 21 – Neural Networks: The Backpropagation Algorithm, Support Vector Machines Unlimited
- Lecture 22 – Reinforcement Learning: Uninformed Combinatorial Search, Q-Learning Unlimited
- Lecture 23 – Reinforcement Learning: Q-Learning Unlimited
- Lecture 24 – Reinforcement Learning: Exploration and Exploitation, Curse of Dimensionality Unlimited
- Lecture 25 – Recommender Systems: The Link-analysis Algorithm, Nearest Neighbour Filtering Unlimited
Instructor
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