Difference Between AI and Machine Learning

Aspect	Artificial Intelligence (AI)	Machine Learning (ML)
Definition	AI is the broad science of making machines perform tasks that require human-like intelligence such as reasoning, problem-solving, perception, and language understanding.	ML is a subset of AI that focuses on enabling machines to learn from data and improve their performance over time without being explicitly programmed.
Scope	Encompasses all aspects of simulating human intelligence, including learning, decision-making, and adaptation.	Focused solely on learning patterns from data to make predictions or decisions.
Goal	To create smart systems that can mimic human thinking and behavior.	To enable machines to learn from past data and make accurate outputs.

Difference Between Data Mining and Machine Learning

Parameter	Data Mining	Machine Learning
Definition	Data mining is a process to extract information from a data set and transform it into an understandable structure for further use.	It is a Technique that concerns the construction and study of systems that can learn from data.
Focus	It focuses on the discovery of unknown properties in the data.	It focuses on prediction, based on known properties learned from training data.
Database Size	It is an automatic or semi-automatic analysis that is performed on large quantities of data.	It is generally performed on small databases to increase accuracy.
Types	Association Rules Classification Clustering Sequential Patterns Sequence Similarity	Supervised Un Supervised Reinforcement