AI Terminology Encyclopedia
Master the essential concepts and terminology of artificial intelligence
Machine Learning
A subset of AI that enables systems to learn from data
Deep Learning
Neural networks with multiple layers for complex pattern recognition
Neural Networks
Computing systems inspired by biological neural networks
Transformer
Architecture using attention mechanisms for sequence processing
Attention Mechanism
Technique allowing models to focus on relevant parts of input
Large Language Model (LLM)
Massive neural networks trained on vast text corpora
Convolutional Neural Network (CNN)
Neural networks specialized for processing grid-like data
Backpropagation
Algorithm for training neural networks by propagating errors backward
Gradient Descent
Optimization algorithm to minimize loss functions
Overfitting
When a model learns training data too well, including noise
Regularization
Techniques to prevent overfitting and improve generalization
Transfer Learning
Reusing pre-trained models for new but related tasks
Fine-tuning
Adapting pre-trained models to specific tasks
Reinforcement Learning
Learning through interaction with environment and rewards
Computer Vision
Enabling computers to understand and interpret visual information
Natural Language Processing (NLP)
Enabling computers to understand and generate human language
Prompt Engineering
Crafting effective inputs to guide AI model outputs
GPT (Generative Pre-trained Transformer)
Family of language models using transformer architecture
BERT (Bidirectional Encoder Representations)
Transformer model that reads text bidirectionally
Generative Adversarial Network (GAN)
Two neural networks competing to generate realistic data
Activation Function
Non-linear functions that determine neuron output