Artificial Intelligence Basics

Study Notes

AI is a branch of computer science that aims to create intelligent machines that can perform tasks requiring human intelligence.
Goals of AI include developing systems that can perceive and understand the environment, reason and make decisions, learn from experience, and interact with humans naturally.

ML is a subset of AI that involves developing algorithms and models enabling computers to learn from data and make predictions or decisions without explicit programming.
ML algorithms are trained on large amounts of data to learn patterns and relationships, making accurate predictions or taking actions.
ML enables machines to automatically learn from data, improve performance, and predict things without human intervention.
Tasks of machine learning can be either predictive or descriptive, employing a set of algorithms that learn without human intervention.

ML technology is used to train machines to perform various actions such as predictions, recommendations, and estimations based on historical data or past experience.
Enables computers to behave like humans by training them with past experience and predicted data.
ML algorithms detect patterns in data, learn from them, and make predictions.

In traditional programming, a computer engineer writes instructions to transform input data into a desired output.
In machine learning, machines are treated like humans, fed with data to learn and interpret, process, and analyze it.
Machine learning algorithms are used to build a predictive model, helping to predict outcomes.

Algorithms: a set of rules and statistical techniques used to learn patterns from data and draw significant information.
Model: a trained representation of the learned relationship between input features and target labels, resulting from the training process.