Machine Learning

Machine learning is a branch of AI where systems learn patterns from data instead of being explicitly programmed.

Deep Learning

Deep learning uses multi-layered neural networks to learn complex patterns directly from raw data.

AI vs ML vs Deep Learning

AI is the broad goal, machine learning is one approach to it, and deep learning is a specific technique within machine learning.

Training

Training is the process of adjusting a model's parameters so its predictions get closer to the correct answers.

Inference

Inference is using a trained model to produce predictions or outputs on new data.

Model

A model is the trained mathematical structure that maps inputs to outputs based on learned patterns.

Parameters

Parameters are the internal values a model learns during training that determine its behavior.

Dataset

A dataset is the collection of examples used to train, validate, or evaluate a model.

Neural Network

A neural network is a layered system of connected nodes that learns to transform inputs into outputs.

GPU

A GPU is specialized hardware that performs the parallel matrix computations AI models rely on far faster than a CPU.