Choose this use case if you wish to develop a model that can understand and classify the attitudes, opinions, and emotions expressed in a text with respect to some topic or the overall contextual polarity of a document. Given a dataset containing chunks of text and their corresponding sentiment labels, you can generate a model that successfully identifies the sentiment of new, unseen text.
Dataset and Feature Group RequirementsThis section specifies the Datasets / Feature Groups requirements to successfully train a Sentiment Analysis model. Feature requirements include recommendations on additional datasets that might enhance model performance.
Training Models - Training Options and MetricsThis section describes all the available model training options that can be used to create a Sentiment Analysis model. You can utilize the metric explanations to better understand how they measure the performance of the model you trained.
Prediction APIThis section discusses the prediction API method so that you could properly generate predictions from the model you deployed.