Sold by: MphasisÂ
Deployed on AWS
Machine Learning based solution which classifies financial news headlines into positive, negative and neutral sentiment categories.
Overview
This solution classifies financial news headlines into positive, negative and neutral sentiments. It uses text analysis, natural language processing, machine learning techniques to predict the sentiment classes. This solution is built around specialized vocabulary encountered in finance and economics. It can be used to identify sentiments of financial headlines and statements from the perspective of potential investors and stakeholders.
Highlights
- Financial Headlines Sentiment Analyzer helps to review financial headlines by predicting their sentiment using Natural Language Processing.
- State-of-the-Art ML model built on specialized financial vocabulary.
- Need customized HyperGraf Machine Learning/NLP solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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Features and programs
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $16.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $8.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $16.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $16.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $16.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $16.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $16.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $16.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $16.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $16.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
This is the version 1.2
Additional details
Inputs
- Summary
- The input dataset should be in csv format.
- The column names in input file should be: Text: Financial News Headlines.
- input file should not contain more than 20 headlines.
- Input MIME type
- text/csv, text/plain, application/zip
https://github.com/Mphasis-ML-Marketplace/Financial-Headlines-Sentiment-Analyzer/tree/main/input
https://github.com/Mphasis-ML-Marketplace/Financial-Headlines-Sentiment-Analyzer/tree/main/input
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
Text | Financial News Headlines, only in English Language.
| Type: FreeText | Yes |
Resources
Vendor resources
Support
Vendor support
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