Machine Learning

AI Terms

Machine Learning

Definition: Machine learning is a subset of artificial intelligence that involves algorithms that learn from data and improve their performance over time.

Detailed Description:

Machine learning algorithms can be categorized into:

Supervised learning: Algorithms trained on labeled data to predict outcomes.
Unsupervised learning: Algorithms that find patterns and relationships within unlabeled data.
Reinforcement learning: Algorithms that learn through trial and error and rewards.

Machine learning is used in various applications, such as:

Image recognition: Identifying objects, faces, and scenes within images.
Natural language processing: Understanding and generating human language.
Recommendation systems: Suggesting products or content based on user preferences.
Predictive analytics: Forecasting future trends.

Related Terms:

FAQs:

What is the difference between machine learning and artificial intelligence?
- Machine learning is a subset of artificial intelligence that focuses on algorithms that can learn from data.
What are the different types of machine learning?
- Supervised learning, unsupervised learning, and reinforcement learning.
What are some challenges in machine learning?
- Data quality, overfitting, and interpretability.

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