Glossary of AI Terms
Stochastic Parrots
A term used to describe large language models that can generate text based on patterns in data.
Emergent Behavior
Complex behaviors that arise from simple rules in AI systems.
Grok
To understand something intuitively or thoroughly.
Reasoning
The process of thinking about something in a logical way.
Co-Pilots
AI systems that assist humans in various tasks.
Agentic AI
AI systems that can act autonomously in a given environment.
Face Detection
A computer technology used to identify and locate human faces in digital images.
Social Distancing Detection
AI systems designed to monitor and ensure social distancing in public spaces.
Histology Images
Microscopic images of tissue samples used in medical diagnosis.
Skin Cancer Classification
The use of AI to classify skin lesions as benign or malignant.
Malaria Detection
AI techniques used to identify malaria parasites in blood samples.
Parkinson's Detection
AI methods for diagnosing Parkinson's disease using various data inputs.
Edge ML
Machine learning models that are deployed on edge devices for real-time processing.
Clustering
A machine learning technique used to group similar data points together.
Transformer Models
A type of deep learning model architecture used for natural language processing tasks.
Neural Networks
Computational models inspired by the human brain, used in machine learning.
Deep Learning
A subset of machine learning involving neural networks with many layers.
Supervised Learning
A type of machine learning where the model is trained on labeled data.
Unsupervised Learning
A type of machine learning where the model finds patterns in unlabeled data.
Reinforcement Learning
A type of machine learning where an agent learns by interacting with its environment.
Overfitting
A modeling error that occurs when a model is too complex and captures noise in the data.
Underfitting
A modeling error that occurs when a model is too simple to capture the underlying trend of the data.
Gradient Descent
An optimization algorithm used to minimize the loss function in machine learning models.
Backpropagation
A method used in neural networks to calculate the gradient of the loss function.
Convolutional Neural Networks
A class of deep neural networks commonly used for analyzing visual imagery.
Recurrent Neural Networks
A class of neural networks designed to recognize patterns in sequences of data.
Natural Language Processing
A field of AI focused on the interaction between computers and humans through language.
Computer Vision
A field of AI that enables computers to interpret and make decisions based on visual data.
Data Augmentation
A technique used to increase the diversity of training data by applying random transformations.
Feature Engineering
The process of selecting, modifying, or creating features to improve model performance.
Hyperparameter Tuning
The process of optimizing the parameters that govern the training process of a model.
Artificial Intelligence
The simulation of human intelligence in machines.
Machine Learning
A subset of AI that enables systems to learn from data.
Deep Learning
A type of machine learning that uses neural networks.