Name: Sentiment Analysis with Deep Learning using BERT
Brand: Coursera
Availability: OnlineOnly
Rating: 4.4 (84 reviews)

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

4.4

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397 个评分

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....

76 - Sentiment Analysis with Deep Learning using BERT 的 84 个评论（共 84 个）

创建者 Prashant B

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Sep 22, 2020

great

创建者 Ovi S

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Jun 2, 2020

Good

创建者 M M A

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Jul 26, 2020

创建者 Venkata N C K

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Jun 1, 2020

创建者 Seema A

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May 23, 2021

All in all good. But it would have been much better with more explanations about the code.

创建者 PRASHANT K

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Jun 28, 2021

It's not up to coursera Standards. Could have been done much much better. Only one good thing can out of it for me that he has provided one or two good reference for reading about BERT.

创建者 Raj P

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Jan 2, 2021

I didn't learn anything new here. This code and explanation is available on the web free of cost.

创建者 Saurabh T

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Jul 23, 2022

Till 'Tokenization and Encoding the data' part, explanation of the code was good. But from 'Setting up BERT pretrained model' part, code explanation was not done properly. Instructor was not giving proper explanation of the BERT parameters that are used in the code.