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Coursera

Sentiment Analysis with Deep Learning using BERT

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.

Status: Model Training
Status: Model Optimization
IntermediateGuided Project2 hours

Featured reviews

FR

5.0Reviewed Oct 11, 2020

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

RA

5.0Reviewed Sep 24, 2021

I like this project and help me a lot to understand how to do Sentiment Analysis with BERT Model

PP

5.0Reviewed Jan 12, 2022

Step by Step explanation of How to practically execute the BERT Reinforced Learning

JK

5.0Reviewed Mar 1, 2025

There is more to learn in this. But the basics are covered well with the practical example.

SS

5.0Reviewed Aug 10, 2020

It was good learning experience... Thanks to coursera :)

NC

4.0Reviewed Jul 18, 2020

I didn't like the platform you use. Rhyme, it's not a good tool.

SN

5.0Reviewed Apr 29, 2021

Thanks, Ari Anastassiou for the wonderful tutorial. Hoping you do a complete course on NLP using BERT soon.

SW

5.0Reviewed May 17, 2020

The instructor explains very well on how to using bert to train a sentiment classifier. Very cool project.

WM

4.0Reviewed Feb 12, 2021

Good instructor, however anyone join this must have at least a knowledge in basic Python Programming and have learned about BERT and fundamental of Natural Language Processing

KA

5.0Reviewed Nov 29, 2020

Very good. Only if it included Inference, then it would have been perfect

SV

5.0Reviewed Jul 23, 2020

Thankyou, really a great course under great instructor.

RK

4.0Reviewed Jun 29, 2020

Required detail explanation and faculy support for error soliving and explroing alternative