Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
Money Transfer Complaints Severity
By:
Latest Version:
2.1
This solution analyzes complaint narratives of money transfer services customers to predict those which may require a monetary compensation.
Product Overview
This is a Natural Language Processing (NLP) based text classification solution that helps identify whether a given consumer complaint requires monetary compensation based on the complaint narrative. A complaint is classified as either requiring monetary relief or if it can be resolved through explanations or non-monetary relief. This classification can be used to decide if monetary compensation should be provisioned and accounted for a given complaint.
Key Data
Version
By
Type
Model Package
Highlights
This solution is trained on a large publicly available dataset of customer complaints about Money transfer, virtual currency, or money service-related complaints and their resolution. It uses text analysis, natural language processing, machine learning techniques to predict if a complaint would require monetary compensation.
This model allows companies to plan for and manage their customer complaints efficiently to enhance the quality of customer service provided by them.
Mphasis HyperGraf is an Omni-channel customer 360 analytics solution. Mphasis HyperGraf is an omnichannel customer 360 analytics solution. Need customized Deep Learning/NLP solutions? Get in touch!
Not quite sure what you’re looking for? AWS Marketplace can help you find the right solution for your use case. Contact us
Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Contact us to request contract pricing for this product.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$10.00/hr
running on ml.m5.large
Model Batch Transform$20.00/hr
running on ml.m5.large
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$0.115/host/hr
running on ml.m5.large
SageMaker Batch Transform$0.115/host/hr
running on ml.m5.large
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on hourly pricing that can vary by instance type. Additional infrastructure cost, taxes or fees may apply.InstanceType | Realtime Inference/hr | |
|---|---|---|
ml.m4.4xlarge | $10.00 | |
ml.m5.4xlarge | $10.00 | |
ml.m4.16xlarge | $10.00 | |
ml.m5.2xlarge | $10.00 | |
ml.p3.16xlarge | $10.00 | |
ml.m4.2xlarge | $10.00 | |
ml.c5.2xlarge | $10.00 | |
ml.p3.2xlarge | $10.00 | |
ml.c4.2xlarge | $10.00 | |
ml.m4.10xlarge | $10.00 | |
ml.c4.xlarge | $10.00 | |
ml.m5.24xlarge | $10.00 | |
ml.c5.xlarge | $10.00 | |
ml.p2.xlarge | $10.00 | |
ml.m5.12xlarge | $10.00 | |
ml.p2.16xlarge | $10.00 | |
ml.c4.4xlarge | $10.00 | |
ml.m5.xlarge | $10.00 | |
ml.c5.9xlarge | $10.00 | |
ml.m4.xlarge | $10.00 | |
ml.c5.4xlarge | $10.00 | |
ml.p3.8xlarge | $10.00 | |
ml.m5.large Vendor Recommended | $10.00 | |
ml.c4.8xlarge | $10.00 | |
ml.p2.8xlarge | $10.00 | |
ml.c5.18xlarge | $10.00 |
Usage Information
Model input and output details
Input
Summary
- The input dataset should be in CSV format.
- The CSV file must have a single column, with different rows containing different customer complaint narratives.
- Each row must contain exactly one consumer narrative
Limitations for input type
A file can have a maximum of 10 records and each record should not have more than 1000 words
Input MIME type
text/csvSample input data
Output
Summary
The output file contains the prediction as to whether monetary relief compensation will be required for the complaint. The prediction column contains only one of two values: “monetary relief” or “non-monetary relief”
Output MIME type
text/csv, text/plainSample output data
Sample notebook
Additional Resources
End User License Agreement
By subscribing to this product you agree to terms and conditions outlined in the product End user License Agreement (EULA)
Support Information
Money Transfer Complaints Severity
For any assistance, please reach out at:
AWS Infrastructure
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.
Learn MoreRefund Policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Customer Reviews
There are currently no reviews for this product.
View allWrite a review
Share your thoughts about this product.
Write a customer review