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學生對 Coursera Project Network 提供的 Sentiment Analysis with Deep Learning using BERT 的評價和反饋

4.5
350 個評分
75 條評論

課程概述

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....

熱門審閱

FR
2020年10月11日

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
2020年7月27日

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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