What is Machine Learning?
The broader field of training algorithms to improve from data without explicit programming.
Definition
Machine Learning (ML) is the broader field of training algorithms to improve from data without explicit programming, enabling systems to learn and adapt automatically.
Purpose
ML aims to create systems that can learn patterns from data and make predictions or decisions on new, unseen information without being explicitly programmed for each specific task.
Function
ML algorithms work by analyzing large datasets to identify patterns, relationships, and trends, then use these insights to make predictions or classifications on new data.
Example
Spotify's ML models learning your listening habits to recommend playlists that match your musical preferences and discovery patterns.
Related
Machine Learning is a subset of Artificial Intelligence and includes techniques like supervised learning, unsupervised learning, and reinforcement learning.
Want to learn more?
If you'd like to go deeper into Machine Learning (ML) —or bring this kind of training to your team— let's talk. I help teams understand and apply these concepts. I'd love to hear from you!
What is Ground Truth in AI?
Ground Truth in AI refers to the accurate, verified, or objectively correct...
What are Embeddings in AI?
Embeddings are dense numerical vector representations that capture the sema...
What is AI?
AI, or Artificial Intelligence, is the broad field of creating systems that...
What does Input mean?
The term Input refers to any information, data, or resource entered into a...
What are AI Guardrails?
AI Guardrails are safety mechanisms, constraints, and filtering systems des...