Sentiment Analysis with Deep Learning using BERT
By Coursera
on Coursera
· Data Science
About This Course
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.
Instructor
Ari Anastassiou
Frequently Asked Questions
How much does Sentiment Analysis with Deep Learning using BERT cost?
Visit the Sentiment Analysis with Deep Learning using BERT course page for current pricing and available discounts.
Who teaches Sentiment Analysis with Deep Learning using BERT?
Sentiment Analysis with Deep Learning using BERT is taught by Ari Anastassiou, Coursera.
What skill level is Sentiment Analysis with Deep Learning using BERT for?
This course is designed for all levels learners.