AI Glossary

Algorithm

A set of instructions or rules that a computer follows to solve a problem or accomplish a task. Think of it like a recipe.

Model

A program that has been trained on a set of data to perform a specific task. It's the 'finished' product of machine learning.

Training

The process of teaching a machine learning model by feeding it data and allowing it to adjust its internal parameters (weights) to minimize errors.

Inference

The phase where a trained model is put to work, making predictions or decisions based on new, unseen data.

Artificial Intelligence (AI)

A broad field of computer science dedicated to creating systems capable of performing tasks that typically require human intelligence.

Machine Learning (ML)

A subset of AI where computers learn from data without being explicitly programmed for specific rules.

Deep Learning (DL)

A specialized type of machine learning that uses neural networks with many layers (hence 'deep') to model complex patterns in data.

Neural Network

A method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain.

Weights

Parameters within a neural network that transform input data within the network's hidden layers. They determine the importance of the input to the output.

Supervised Learning

A type of machine learning where the model is trained on a labeled dataset (data with known answers).

Unsupervised Learning

A type of machine learning where the model tries to find patterns and relationships in unlabeled data.

Pattern Recognition

The automated recognition of patterns and regularities in data.

eCampus Ontario AI Fundamentals
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What is AI: The "Black Box" Opened

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25-30 Minutes

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Learning Objectives

  • 1. between Rule-Based Computing (The Soldier) and AI (The Scout).
  • 2. the hierarchy: AI vs. Machine Learning vs. Deep Learning.
  • 3. core vocabulary: Algorithm, Training, Model, and Inference.
  • 4. why "Rules" fail in the real world using the Excel Error simulation.
  • 5. your first simple Computer Vision model using stock data.