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#44 Project Jupyter and Interactive Computing

DataFramed

CHAPTER

Why Multi Task Learning Is So Effective?

Multi task learning is only effective if the model is asked to learn tasks that are related. While single task ulgarithms struggle with noisy labels, multitask ulgaritms are more robust to noise. Multitas models also tend to be more efficient in production. A multitas model can give you multiple predictions, while it needs to process the input data only once. And finally, multitas models can give you insight into task relations, which, as prety got it, puts current news in perspective.

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