Sold by: MphasisÂ
Deployed on AWS
This solution helps in automatic labelling and correction of label errors in a sentiment analysis dataset
Overview
This solution takes in the unlabeled dataset and obtains weak labels using BERT based pre-trained model for sentiment classification. It also identifies the errors present in the generated weak labels using confidence learning methods using the predicted probability scores.The output contains orginal dataset split into two subsets, 1) Subset 1 of Clean labels (positive, negative or neutral) that could be directly used for downstream applications 2) Subset 2 of data that will have label errors that can be further subjected to manual validation
Highlights
- This solution leverages a data-centric approach to find the label errors in a sentiment classification dataset which helps to improves the quality of data and is extremely pertinent to any downstream supervised model-centric workflow.
- This solution can be used to obtain automated sentiment class labels for 3 sentiment classes: positive, negative and neutral, in cases where you have only unlabelled dataset to start with. It can be applied to datasets such are product reviews, tweets, social- media posts and financial news to capture the sentiment of the provided text.
- PACE - ML is Mphasis Framework and Methodology for end-to-end machine learning development and deployment. PACE-ML enables organizations to improve the quality & reliability of the machine learning solutions in production and helps automate, scale, and monitor them. Need customized Machine Learning and Deep Learning solutions? Get in touch!
Details
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Delivery method
Latest version
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
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.
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Vendor terms and conditions
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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
Bug fixes
Additional details
Inputs
- Summary
The user needs one csv file containing a text column that has the sentiment analysis data
- Input MIME type
- text/csv
https://github.com/Mphasis-ML-Marketplace/Automated-Sentiment-Label-Correction/blob/main/input/input.csv
https://github.com/Mphasis-ML-Marketplace/Automated-Sentiment-Label-Correction/blob/main/input/input.csv
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
input.csv | The csv contains a single column 'text' containing of sentiment analysis data. | Type: FreeText | Yes |
Resources
Vendor resources
Support
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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