20 AI Terimi ve Açıklaması

Al: The overarching world of Artificial Intelligence, transforming industries.

ML: Machine Learning's role in shaping intelligent systems.

Deep Learning: Neural networks for human-like thinking.

Neural Network: Mimicking human brain functions for learning.

Supervised Learning: Teaching computers with labelled examples.

Unsupervised Learning: Machines finding patterns without labels.

Reinforcement Learning: Trial-and-error learning for machines.

NLP: Tech enabling computers to understand human language.

Computer Vision: Machines interpreting visual information.

Chatbot: Conversational Al for customer support and more.

IOT: Devices connected, sharing data for smart applications.

Cloud Computing: Remote storage, management, and data processing.

Bias in Al: Addressing unintentional biases in algorithms.

Algorithm: Core of Al, the building block for intelligent systems.

Data Mining: Extracting patterns and insights from vast datasets.

Big Data:Navigating challenges with massive and diverse data.

Robotics: Merging Al with physical machines for automation.

Algorithmic Fairness: Ensuring fairness and avoiding bias in Al.

Transfer Learning: Applying knowledge for enhanced Al efficiency.

Edge Computing: Localised Al implementation for efficiency.

Explainable Al: Making Al decisions transparent and understandable.

GANS: Al creating realistic data through adversarial networks.

Edge Al: Localised Al for reduced reliance on centralised servers.

Al Ethics: Guiding principles for responsible Al development