Sentiment Analysis with Deep Learning using BERT

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在此指導項目中,您將:
120 minutes
中級
無需下載
分屏視頻
英語(English)
僅限桌面

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.

您要培養的技能

  • Natural Language Processing

  • Deep Learning

  • Machine Learning

  • Sentiment Analysis

  • BERT

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