In a scenario where both input and output data are available but are not directly linked, which type of learning approach would be suitable to find the hidden patterns?
- Supervised Learning
- Unsupervised Learning
- Reinforcement Learning
- Semi-Supervised Learning
Unsupervised Learning is the appropriate approach when you have input and output data that are not directly linked. It helps discover hidden patterns, clusters, or relationships within the data without labeled examples to guide the learning process.
Loading...
Related Quiz
- Text data from social media platforms, such as tweets or Facebook posts, is an example of which type of data?
- The _______ is a measure of the relationship between two variables and ranges between -1 and 1.
- Your organization wants to move away from traditional batch processing of data and is looking for a tool that can offer in-memory processing for faster analytics. Which Big Data framework would you recommend?
- The process of converting a trained machine learning model into a format that can be used by production systems is called _______.
- What is the primary challenge associated with training very deep neural networks without any specialized techniques?