Examining historical data to understand what has happened in the past.
Using data and statistical algorithms to identify the likelihood of future outcomes.
Recommending actions to optimize outcomes based on analysis.
Algorithms that enable systems to learn and improve from experience.
Natural Language Processing (NLP): Enabling machines to understand, interpret, and generate human-like language.
Allowing machines to interpret and make decisions based on visual data.
AI often involves data analytics, particularly machine learning, where models are trained on large datasets to make predictions or decisions.
Data analytics provides the foundation for training AI models by supplying the necessary data for learning and improving performance.
AI systems generate new data as they operate, contributing to a feedback loop that can be further analyzed to enhance the system's performance.