Karteikarten: Fundamentals of Artificial Intelligence — 12 Karten

Artificial Intelligence — definition?

Simulation of human intelligence by machines.

Course objectives — overview?

Introduces AI, its structure, and development history.

Basic AI principles — key?

Reasoning, knowledge representation, planning, learning, NLP, perception, robotics.

Deep learning — techniques?

Neural networks, especially deep and convolutional types.

AI applications — examples?

Healthcare, autonomous vehicles, NLP, daily tech.

Ethics in AI — main issues?

Bias, transparency, accountability, privacy.

Supervised learning — data type?

Labeled data for predicting outputs.

Unsupervised learning — focus?

Finding patterns in unlabeled data.

Reinforcement learning — mechanism?

Learning via rewards in an environment.

Neural networks — inspiration?

Inspired by human brain's neuron connections.

Convolutional neural networks — use?

Image processing and spatial feature recognition.

Backpropagation — purpose?

Training neural networks by error correction.