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学生对 Coursera Project Network 提供的 Sentiment Analysis with Deep Learning using BERT 的评价和反馈

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350 个评分
75 条评论

课程概述

In this 2-hour long project, you will learn how to analyze a dataset for sentiment analysis. You will learn how to read in a PyTorch BERT model, and adjust the architecture for multi-class classification. You will learn how to adjust an optimizer and scheduler for ideal training and performance. In fine-tuning this model, you will learn how to design a train and evaluate loop to monitor model performance as it trains, including saving and loading models. Finally, you will build a Sentiment Analysis model that leverages BERT's large-scale language knowledge. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

热门审阅

FR
Oct 11, 2020

Clean, clear and helpful. Thanks a lot!\n\nWould also be nice to see the approaches to tune BERT for the particular task (e.g. custom tokenization, pre-processing of data, etc.)

GB
Jul 27, 2020

Thanks to Mr.Ari Anastassiou\n\nSentiment Analysis with Deep Learning using BERT! is been really a wonderful project .Enjoyed it

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