AI Glossary & Dictionary for “O”
Find the Flux+Form AI glossary & dictionary to help you make sense of common AI terms. Below you can find a AI Glossary & Dictionary for “O”:
Object Detection
A computer vision task that identifies and locates specific objects within images or video. Picture a security system that can spot and track specific items or people in surveillance footage.
Object Recognition
A technique that identifies what an object is within an image or video stream. Similar to how a quality control system might identify different products on a conveyor belt.
Objective Function
In the context of machine learning, a mathematical function that defines what a model aims to optimize. Like a scoring system that tells you how well you’re performing at a specific task.
Offline Learning
A learning approach where models train on a fixed dataset before deployment. Imagine a student studying a complete textbook before taking a final exam.
One-Hot Encoding
A technique that represents categorical variables as binary vectors. Picture converting a list of colors into a format where each color gets its own true/false column.
One-Shot Learning
A capability where models can learn from just one or very few examples. Like a system that can recognize a new face after seeing it just once.
Online Learning
A learning method where models update continuously as new data arrives. Similar to a recommendation system that updates its suggestions based on your latest interactions.
Optimization
The process of adjusting model parameters to minimize errors or maximize performance. Picture fine-tuning a radio until you get the clearest possible signal.
Optimizer
An algorithm that implements specific strategies for updating model parameters during training. This works like a coach adjusting a team’s strategy based on their performance.
Orthogonal
In the context of machine learning, features or vectors that are completely independent of each other. Imagine different aspects of a movie – genre, length, release date – that don’t influence each other.
Outlier Detection
A technique for identifying data points that significantly differ from the majority. Like a quality control system flagging products that don’t meet normal specifications.
Output Layer
The final layer of a neural network that produces the model’s predictions or decisions. Similar to the final stage of an assembly line where the finished product emerges.
Overfitting
A condition where a model learns training data too precisely, hurting its ability to generalize. Picture a student who memorizes test answers without understanding the underlying concepts.
Oversampling
A technique that creates additional copies of minority class examples to balance dataset distributions. Like making extra copies of rare examples to ensure they’re properly represented in training.
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