Sentiment analysis using deep learning with Azure Machine Learning
NOTE This content is no longer maintained. Visit the Azure Machine Learning Notebook project for sample Jupyter notebooks for ML and deep learning with Azure Machine Learning.
Link to the Microsoft DOCS site
The detailed documentation for this sentiment analysis example includes the step-by-step walk-through: https://docs.microsoft.com/azure/machine-learning/preview/scenario-sentiment-analysis-deep-learning
Link to the Gallery GitHub repository
The public GitHub repository for this sentiment analysis example contains all the code samples: https://github.com/Azure/MachineLearningSamples-SentimentAnalysis
Sentiment analysis is a well-known task in the realm of natural language processing. Given a set of texts, the objective is to determine the sentiment of that text. This example demonstrates the use of Keras to perform sentiment analysis from movie reviews.
Key components needed to run this example
- An Azure account (free trials are available).
- An installed copy of Azure Machine Learning Workbench with a workspace created.
- The deployment part of this example is run on a Linux DSVM.
Data / Telemetry
Sentiment Analysis collects usage data and sends it to Microsoft to help improve our products and services. Read our privacy statement to learn more.
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.
When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (for example, label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.