Machine Learning
Definition
Machine Learning (ML) is a type of artificial intelligence (AI) that allows a computer to learn from data without being explicitly programmed. It uses algorithms and statistical models to perform tasks by making predictions or decisions without human intervention.
Explain Like I'm 5
Imagine if your toy car could learn how to avoid crashing into walls by itself after a few bumps and bruises. Machine learning is like that, but for computers. They learn from their mistakes and get better over time.
Visualization
Digging Deeper
Machine learning involves the use of algorithms that can learn from and make decisions or predictions based on data. These algorithms operate by building a model from an example training set of input observations in order to make data-driven predictions or decisions, rather than strictly following static program instructions.
Machine learning is categorized mainly into three types: supervised learning, where the model learns from labeled data; unsupervised learning, where the model learns from unlabeled data; and reinforcement learning, where the model learns by interacting with its environment and receiving rewards or punishments based on its actions.
Examples of machine learning include email filtering, detection of network intruders, and computer vision, which allows computers to understand images in a similar way to humans.
Applications
- Healthcare: Machine Learning can be used for disease detection, drug discovery, patient care etc.
- Finance: Financial institutions use ML for credit scoring, algorithmic trading etc.
- Marketing: ML helps in predictive analysis to understand customer behavior.
- Transportation: Self-driving cars use machine learning to navigate safely.
- Speech recognition: Digital assistants like Siri or Alexa use machine learning to understand and respond to human speech.
Learn More
- Machine Learning - Wikipedia
- Intro to Machine Learning - Udacity
- Understanding Machine Learning: From Theory to Algorithms - Book