Sentiment Analysis using Deep Learning

By for September 18, 2017

Report Abuse
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 polarity of that text. The objective of this lab is to use CNTK as the backend for Keras and implement sentiment analysis from movie reviews.
1. The **detailed documentation** for this real world scenario includes the step-by-step walkthrough at: https://github.com/Azure/MachineLearningSamples-SentimentAnalysis/blob/master/scenario-sentiment-analysis-deep-learning.md 2. For code samples, click the "**View Project**" icon on the right and visit the project GitHub repo. 3. Key components needed to run this scenario: - An Azure account (free trials are available) - An installed copy of Azure Machine Learning Workbench following the quick start installation guide to install the program and create a workspace - For operationalization, it is best if you have Docker engine installed and running locally. If not, you can use the cluster option but be aware that running an Azure Container Service (ACS) can be expensive. - This Solution assumes that you are running Azure Machine Learning Workbench on Windows 10 with Docker engine locally installed. If you are using macOS the instruction is largely the same. - Sentiment Analysis code samples located in the project GitHub repo.