What is sequential processing in machine learning?
Sequential processing in machine learning refers to the method of processing data in a specific order, often used in time series analysis.
Can you give me an example of where this is applied?
Sure! It's commonly used in natural language processing, like in language models that predict the next word based on previous words.
What are the advantages of using sequential processing?
The main advantages include improved accuracy in predictions and the ability to capture temporal dependencies in data.
Are there any limitations to this approach?
Yes, sequential processing can be computationally intensive and may struggle with long sequences due to vanishing gradients.
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