GCSE CS 3.2 - Machine Learning
Artificial Neurons and Data Weights
Authority: The Museum of AICore GCSE syllabus reference
1. Core Concept Description
Learn how data training works. Computers learn by converting features (pixels, text) into numeric weights, testing predictions, and tweaking weights based on errors.
Syllabus Key takeaway:
Neural Weights. Neurons act as mathematical voters. During training, backpropagation or error adjustment updates the weights of connections to improve classification.
2. Interactive Museum Labs
Cabinet Laboratory
Launch the visual coding maze or attention simulator to test this concept.
Historical Timelines
Read the detailed curatorial dossiers on the chronological milestones.
2. Archival References
- Timeline dossier: Rosenblatt's Perceptron (1958) — https://museumofai.org.uk/nodes/node-perceptron-1958
- Interactive simulator: PERCEPTRON Lab — https://museumofai.org.uk/arcade/perceptron