Vjblom
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Summary Knowledge Organization
Summary based on lectures. I got an 8.5 for the exam. This course covers the general principles and methods that form the foundation of information organization and knowledge-intensive processes, as well as the contexts in which they can be applied and the interaction with users. The lecture topics include knowledge modeling, ontologies, logic, controlled natural language, Semantic Web and Linked Data, as well as knowledge maintenance and evaluation, in addition to guest lectures on speci...
- Summary
- • 56 pages •
Summary based on lectures. I got an 8.5 for the exam. This course covers the general principles and methods that form the foundation of information organization and knowledge-intensive processes, as well as the contexts in which they can be applied and the interaction with users. The lecture topics include knowledge modeling, ontologies, logic, controlled natural language, Semantic Web and Linked Data, as well as knowledge maintenance and evaluation, in addition to guest lectures on speci...
Summary Deep Learning (MSc AI)
Based on lectures. I got a 9 for the exam! Deep learning becomes the leading learning and modeling paradigm in machine learning. During this course, we will present basic components of deep learning, such as: - different layers (e.g., linear layers, convolutional layers, pooling layers, recurrent layers); - non-linear activation functions (e.g., sigmoid, ReLU); - backpropagation; - learning algorithms (e.g., ADAM); - other (e.g., dropout). Further, we will show how to build deep ar...
- Summary
- • 82 pages •
Based on lectures. I got a 9 for the exam! Deep learning becomes the leading learning and modeling paradigm in machine learning. During this course, we will present basic components of deep learning, such as: - different layers (e.g., linear layers, convolutional layers, pooling layers, recurrent layers); - non-linear activation functions (e.g., sigmoid, ReLU); - backpropagation; - learning algorithms (e.g., ADAM); - other (e.g., dropout). Further, we will show how to build deep ar...
Summary Multi-agent systems (MSc AI)
Based on lecture content. In Multi-agent systems (MAS) one studies collections of interacting, strategic and intelligent agents. These agents typically can sense both other agents and their environment, reason about what they perceive, and plan and carry out actions to achieve specific goals. In this course we introduce a number of fundamental scientific and engineering concepts that underpin the theoretical study of such multi-agent systems. In particular, we will cover the following top...
- Summary
- • 81 pages •
Based on lecture content. In Multi-agent systems (MAS) one studies collections of interacting, strategic and intelligent agents. These agents typically can sense both other agents and their environment, reason about what they perceive, and plan and carry out actions to achieve specific goals. In this course we introduce a number of fundamental scientific and engineering concepts that underpin the theoretical study of such multi-agent systems. In particular, we will cover the following top...
Summary Evolutionary Computing (MSc AI VU)
Summary based on both lectures and book. Including some exam questions. I got an 8.5 for the exam. This course is about constructing, applying and studying algorithms based on the Darwinian evolution theory. Driven by selection (survival of the fittest, mating of the fittest) and randomised reproduction (mutation, recombination), an evolutionary process is being emulated and solutions for a given problem are being "bred". During this course, various flavours within evolutionary computing are ...
- Book
- Summary
- • 131 pages •
Summary based on both lectures and book. Including some exam questions. I got an 8.5 for the exam. This course is about constructing, applying and studying algorithms based on the Darwinian evolution theory. Driven by selection (survival of the fittest, mating of the fittest) and randomised reproduction (mutation, recombination), an evolutionary process is being emulated and solutions for a given problem are being "bred". During this course, various flavours within evolutionary computing are ...
Samenvatting - Brain Imaging (P_MBRIMAG_AI)
Samenvatting op basis van de lectures, aanvullende videos en literatuur van de course.
- Summary
- • 91 pages •
Samenvatting op basis van de lectures, aanvullende videos en literatuur van de course.
Samenvatting - Knowledge Representation (XM_0059)
Samenvatting op basis van de lectures van de course.
- Summary
- • 73 pages •
Samenvatting op basis van de lectures van de course.
Samenvatting - Skills for AI (XM_0077)
Samenvatting op basis van de lectures (slides) van de course.
- Summary
- • 63 pages •
Samenvatting op basis van de lectures (slides) van de course.