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Sentiment Analysis using Dell APEX File Storage for AWS and Amazon SageMaker
Executive summary Solution Architecture Solution Overview
Solution Overview
Solution Setup
Solution Scope
Solution Validation Conclusion References

Solution Scope

Home > APEX > Storage > White Papers > Sentiment Analysis using Dell APEX File Storage for AWS and Amazon SageMaker > Solution Scope

Solution Scope

  • Train a BERT model for text classification using Dell APEX File Storage for AWS and Amazon SageMaker. The major components used in this example are:

    Amazon SageMaker

    Amazon SageMaker Python SDK allows you to launch training jobs with ease using just a few lines of code.
     

    BERT

    BERT is a transformer-based machine learning technique for Natural Language Processing (NLP). It is a pre-trained deep bidirectional representation from the unlabeled text by jointly conditioning on both left and right context.
     

    IMDB Dataset

    This notebook trains a sentiment analysis model to classify movie reviews as positive or negative, based on the text of the review. The dataset contains over 50,000 movie reviews collected from the IMDB movie database.
     

    Storage

    Transfer and storage of the dataset resides on Dell APEX File Storage. An NFS share is mounted locally where the data is gathered for training. The trained model is also saved on Dell APEX File Storage for reuse.