Published: 29 January 2020
Summary
Machine learning can be supervised, unsupervised or reinforced. Application leaders must learn how to effectively employ each of these machine learning types, and recognize which types of machine learning align with their use cases.
Included in Full Research
- Use Supervised Learning for Classification or Prediction Problems
- Example Use Cases for Supervised Learning
- Use Unsupervised Learning for Clustering Problems
- Example Use Cases for Unsupervised Learning:
- Build Expertise That Will Be Able to Capitalize on the Potential of Reinforcement Learning
- Example Use Cases for Reinforced Learning:
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