Artificial Intelligence and Machine Learning Concepts

These flashcards cover key concepts, paradigms, and terminology related to Artificial Intelligence and Machine Learning as discussed in the lecture notes.

Artificial Intelligence

The simulation of human intelligence processes by machines, particularly computer systems.

Computer Vision

A subfield of artificial intelligence that enables machines to process, analyze, and interpret visual inputs from the world.

Supervised Learning

A type of machine learning where the model is trained on labeled data.

Unsupervised Learning

A type of machine learning where the algorithm learns from unlabeled data without any predefined outputs or target variables.

Deep Learning

A subset of machine learning involving neural networks with many layers to analyze various data types.

Convolutional Neural Networks (CNNs)

A class of deep learning algorithms particularly effective for image classification and visual recognition tasks.

Model Evaluation Metrics

Standard performance measures used to assess the accuracy and effectiveness of machine learning models.

Data Processing

The method of converting raw data into a format suitable for analysis by machine learning algorithms.

Regression

A machine learning task that predicts a continuous numerical value.

Classification

A machine learning task that assigns input data into discrete categories.

Clustering

An unsupervised learning technique that groups similar data points together based on shared characteristics.

Dimensionality Reduction

The process of reducing the number of input variables in a dataset, retaining essential structures and patterns.

Semi-Supervised Learning

A machine learning paradigm that uses both labeled and unlabeled data for training.

Neural Networks

Computational models inspired by the human brain, consisting of interconnected nodes or 'neurons' to process data.

Support Vector Machines

A supervised learning algorithm that separates classes using an optimal hyperplane.

Random Forest

An ensemble learning method that combines multiple decision trees to enhance accuracy.

Image Recognition

The ability of a system to identify and classify objects or features within an image.

Facial Recognition

A technology capable of identifying or verifying a person from a digital image or video frame.