Machine learning is a branch of artificial intelligence that gives computers the ability to learn without being explicitly programmed. It can automatically process the large quantities of data that humans have a difficult time doing. Machine learning is all around us and you may not even know it.
- Siri and Alexa use natural language processing to translate human speech.
- Facebook will automatically tag your friends in photos by using facial recognition.
- Your email provider will use machine learning to identify spam.
- The Department of Health uses it to predict disease outbreaks.
There's complex math involved with machine learning, which is what makes it so powerful.
Supervised learning is the most practical type of machine learning. Supervised learning always has a target variable (Y), which can also be called a "dependent variable" or "response variable", and input variables (X). It's called supervised because algorithms learn from a training data set. Some examples of supervised learning problems are classification and regression.
In unsupervised learning there is no target variable(s), only input variables. Algorithms are fed unlabeled data to find patterns and structures. Some examples of unsupervised learning problems are clustering and association rules.
Machine Learning Types:
- Regression & Forecasting
- Impact Analysis
- Anomaly Detection
- Natural Language Processing
- Image Recognition
- Sentiment Analysis
- And many more!
For a complete list of machine learning types available through our API, and what's coming soon, check out our Product Overview page.