// TECHNOLOGY INDEX
Artificial Intelligence For Your Business
The main goal in supervised learning is to learn a model from labeled training data that allows us to make predictions about unseen or future data. Examples:
- Speech Recognition
- Image Recognition
- Predictive Maintenance
Unsupervised learning is a type of machine learning algorithm used to draw inferences from datasets without human intervention, in contrast to supervised learning where labels are provided along with the data.
Reinforcement learning is a type of machine learning technique where a computer agent learns to perform a task through repeated trial and error interactions with a dynamic environment. Examples:
- Robotics
- Scheduling
- Calibration
Deep learning allows machines to solve complex problems even when using a data set that is very diverse, unstructured and inter-connected. Examples:
- Automated Driving
- Medical Research
- Industrial Automation
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