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Sentiment Analysis (8 results) showing 1 - 8



hyScore.io is an independent provider of innovative Natural Language Processing (NLP) solutions in multiple languages combined with AI and Machine Learning (ML). With hyScore analyze you use a NLP solution that provides valuable insights from any text or website in real-time as a structured JSON...

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This SageMaker model package provides a REST api to analyze the sentiment of English sentences. The API accepts input as JSON, CSV or plain text, and identifies the sentiment (positive or negative) and provides a confidence level (float number from 0 to 1). We welcome your feedback at...

Model Package - Fulfilled on Amazon SageMaker

  • Version 1.0
  • Sold by KNIME

Predicts the sentiment of forum reviews. Provide the text in JSON format. The model was trained using an open dataset of airline reviews. The model is deployed using a KNIME workflow (www.knime.com).

Model Package - Fulfilled on Amazon SageMaker

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Text Tagger creates models from user-provided training sets, such as customer reviews, newspaper articles, academic papers, and business documents. Text Tagger can create models based on training sets with as few as 100 examples per category, though larger training sets will generate more robust...

Algorithm - Fulfilled on Amazon SageMaker


In this algorithm we'll be applying deep learning techniques to the task of sentiment analysis. Sentiment analysis can be thought of as the exercise of taking a sentence, paragraph, document, or any piece of natural language, and determining whether that text's emotional tone is positive or...

Algorithm - Fulfilled on Amazon SageMaker


Get sentiment analysis results with score for the given text. Find out the tone of a user comment or post. This is helpful when you have a lot of unstructured data like Twitter comments or user feedback where you need to sort or identify the most favorable and most unfavorable comments.

Model Package - Fulfilled on Amazon SageMaker


Get the emotions of a paragraph of text. What emotions are in this text...? Detect the emotions of a paragraph of text and understand its tones. This mood detector returns a score for each of six emotions: disgust, sadness, anger, joy, surprise, and fear.

Model Package - Fulfilled on Amazon SageMaker

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Mphasis HyperGraf is an Omni-channel customer 360 analytics solution. Sentiment Analyzer expresses a positive, negative and neutral sentiment given a text like tweets, messages, emails, blogs, reviews, forum discussions, and social posts. This module uses text analysis, natural language processing,...

Model Package - Fulfilled on Amazon SageMaker

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