AI Glossary & Dictionary for “P”
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 “P”:
Padding
A technique that adds extra values to data to maintain consistent dimensions. Similar to adding margins to a photo to make it fit a standard frame size.
Parallel Processing
The simultaneous execution of multiple AI computations across different processors. Picture multiple chefs working on different parts of a meal simultaneously to complete it faster.
Parameter
A variable in a model that is learned during training. These are like the adjustable settings that a system fine-tunes as it learns from examples.
Parameter Sharing
A technique where multiple parts of a model use the same parameters to reduce complexity. Imagine using the same set of image filters to analyze different parts of a photo.
Parser
A component that analyzes and interprets the structure of text or code. Like a language expert breaking down sentences to understand their grammatical structure. Make.com uses parsers to separate JSON.
Partial Derivative
In machine learning, a measurement of how changes in one variable affect the output while holding other variables constant. Picture adjusting one control on a mixing board to see how it affects the sound.
Path Planning
An AI technique for finding optimal routes through complex spaces. Similar to a delivery robot calculating the best path through a warehouse while avoiding obstacles.
Pattern Recognition
The ability to identify recurring structures or regularities in data. Like a system learning to spot specific customer behaviors that indicate buying interest.
Perceptron
A basic type of artificial neuron that makes binary decisions based on weighted inputs. Picture a simple digital gate that decides whether to activate based on combined signal strengths.
Performance Metric
A measure used to evaluate how well a model performs its intended task. Imagine a scorecard that rates different aspects of a system’s effectiveness.
Pipeline
A sequence of data processing steps that transform raw input into final output. Like an assembly line where data gets cleaned, transformed, and analyzed in sequence.
Plateau
In the context of training, a period where model performance stops improving. Similar to hitting a skill ceiling where traditional practice no longer yields improvement.
Policy
In reinforcement learning, a strategy that determines what actions to take in different situations. Think of it as a playbook that guides decision-making based on current conditions.
Pooling
A technique that reduces data dimensions by combining nearby values. Picture summarizing a high-resolution image into a lower-resolution version while keeping important features.
Position Embedding
A method to incorporate position information into sequence models. Like adding location tags to words so the model knows their position in a sentence.
Post-Processing
Additional computations performed on a model’s output to refine or format results. Similar to editing a photo after it’s been taken to enhance its appearance.
Precision
A metric that measures the proportion of correct positive predictions among all positive predictions. Picture a spam filter’s accuracy in correctly identifying actual spam emails.
Prediction
A model’s output or estimate for a given input. Like a weather forecast based on current atmospheric conditions.
Predictive Analytics
Techniques that use historical data to make future predictions. Similar to analyzing past sales patterns to forecast future demand.
Pre-Processing
Data preparation steps performed before training or inference. Imagine preparing ingredients before cooking – washing, cutting, and measuring everything needed.
Pre-Training
Initial training on a general dataset before fine-tuning for specific tasks. Like giving a robot basic movement skills before teaching it specialized tasks.
Probabilistic Model
A model that expresses predictions as probability distributions rather than single values. Imagine a system that doesn’t just predict rain or no rain, but gives percentage chances for different weather conditions.
Probability Distribution
In machine learning, a function that describes the likelihood of different possible outcomes. Like a sophisticated betting system that assigns odds to various possibilities.
Progressive Training
A training approach that gradually increases task complexity. Similar to learning to play music by mastering simple pieces before attempting complex ones.
Prompt Engineering
The practice of designing effective input prompts to achieve desired outputs from language models. Like crafting the perfect question to get the most helpful response from an AI assistant.
Pruning
The removal of unnecessary connections or components from a trained model. Picture trimming away unused pathways in a neural network to make it more efficient.
PyTorch
A popular deep learning framework that provides tools for building and training neural networks. Like a specialized workshop filled with tools for building AI systems.
This concludes AI Glossary & Dictionary for “PN”
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