AI Glossary & Dictionary for “N”
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 “N”:
Naive Bayes
A classification algorithm that treats each feature as independent when calculating probabilities. Picture a spam filter examining each word in an email separately, assuming no relationships between words, to determine if it’s spam.
Named Entity Recognition
A technique that identifies and classifies key elements like names, organizations, and locations in text. Similar to highlighting every company name, person, and place mentioned in a document with different colored markers.
Natural Language Processing
The branch of AI focused on enabling computers to understand and generate human language. Imagine teaching a computer not just to read words, but to understand context, sentiment, and meaning like a human translator would.
Nearest Neighbor
A classification method where models make predictions based on the most similar examples in their training data. Like a real estate system that estimates a house’s value by finding the most similar houses that recently sold.
Negative Sampling
A training technique that reduces computational complexity by using only a selected subset of negative examples. This works like teaching object recognition using many positive examples but only a few carefully chosen counterexamples.
Neural Architecture Search
An automated process for designing optimal neural network structures. Picture a system that experiments with thousands of different neural network designs to find the most efficient one for a specific task.
Neural Cache
A system that stores previous computations to speed up processing of similar inputs. Like a short-term memory that remembers recent calculations to avoid repeating work unnecessarily.
Neural Coding
The method by which information is represented and transmitted between artificial neurons. This parallels how computers encode complex information into patterns of numbers for processing.
Neural Network
A computing system that learns through interconnected nodes adjusting their connections’ strengths. Think of it like a self-improving digital brain that strengthens or weakens connections based on experience.
Neural Style Transfer
A technique that applies the artistic elements of one image to another while preserving its content. Much like an artist repainting your portrait in the style of a famous artwork while keeping it recognizable.
Neuron
In artificial neural networks, a processing unit that receives inputs and generates output based on learned parameters. This resembles a tiny decision-maker that weighs information according to its training.
No-Code Tools — No-code tools are platforms that allow users to build applications, automate tasks, and create digital solutions without writing traditional code. Using no-code tools is like building with LEGO blocks—each piece snaps together easily, letting you create complex structures without needing engineering skills.
Node Embedding
A technique that converts network nodes into dense vector representations capturing their relationships. Picture converting social media users into numerical coordinates where similar users are placed closer together.
Noise
In the context of machine learning, unwanted variations or errors in training data that can confuse model learning. It’s like trying to teach a system to recognize cats in photos, but some images have misleading shadows or artifacts.
Noise Injection
A training technique that deliberately adds random variations to make models more robust. Similar to practicing facial recognition under different lighting conditions to ensure reliability.
Non-Linear
Within neural networks, functions that enable models to learn complex patterns beyond simple proportional relationships. Picture an AI learning to recognize emotions in text, where word combinations can create entirely new meanings.
Non-Maximum Suppression
A method that filters redundant object detections by removing overlapping boxes with lower confidence scores. Like removing duplicate pins from a map when multiple people have marked the same location.
Non-Parametric Model
A model that makes predictions without assuming a fixed structure in the underlying data. Imagine a system that adapts its approach based on the training data rather than forcing data to fit a predetermined pattern.
Normalization
A process that adjusts feature values to a comparable scale to improve model training efficiency. This is like converting different measuring systems to a single standard for consistent comparison.
Normalizing Flow
A technique that transforms complex data distributions into simpler ones that are easier for models to work with. Picture a system that can convert complicated, messy data patterns into simpler, more manageable forms.
Numpy
A fundamental Python library that enables efficient manipulation of large numerical datasets and matrices. Consider it as the mathematical engine that powers many AI computations.
This concludes the AI Glossary & Dictionary for “N.”
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