Arik Chakma
274082fd77
* refactor: clean to roadmap content * refactor: move shared helpers into scripts/lib
8 lines
689 B
Markdown
8 lines
689 B
Markdown
# Semi-Supervised Learning
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Semi-supervised learning is a type of machine learning where the training data contains both labeled and unlabeled examples. The goal is to leverage the information from the unlabeled data to improve the performance of a model that would otherwise be trained solely on the labeled data. This approach is particularly useful when obtaining labels is expensive or time-consuming, but unlabeled data is readily available.
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Visit the following resources to learn more:
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- [@article@What is Semi-Supervised Learning?](https://www.ibm.com/think/topics/semi-supervised-learning)
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- [@video@What is Semi-Supervised Learning?](https://www.youtube.com/watch?v=C3Lr6Waw66g) |