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.
Mphasis DeepInsights Document Classifier
By:
Latest Version:
3.1
This solution categorizes different documents types like contract documents, broker submissions, invoices, etc.
Product Overview
Document Classifier is a Natural Language Processing based text classification model which analyzes the document text to identify the document type. It ingests documents in pdf format and gives the document type as a text string. Supported Document Types are: 1. Commercial Invoices 2. Broker Submission Document 3. Insurance Claim Forms 4. Contract Document The model works well with above document types and can be extended to classify other documents types as well. It can be applied in various use cases like spam filtering, triaging and document indexing
Key Data
Version
By
Type
Model Package
Highlights
Document classification helps in indexing of different kinds of documents, which improves the turnaround time for such tasks. The automated identification of the document type saves a lot of time and effort for such repetitive tasks, freeing up the analysts time for other important tasks.
Natural Language Processing based Text Modeling ensures high accuracy. The model can be scaled to process high volumes of documents.
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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$4.00/hr
running on ml.m5.large
Model Batch Transform$8.00/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 | $4.00 | |
ml.g4dn.4xlarge | $4.00 | |
ml.m5.4xlarge | $4.00 | |
ml.m4.16xlarge | $4.00 | |
ml.m5.2xlarge | $4.00 | |
ml.p3.16xlarge | $4.00 | |
ml.r5.large | $4.00 | |
ml.g4dn.2xlarge | $4.00 | |
ml.m4.2xlarge | $4.00 | |
ml.r5.12xlarge | $4.00 | |
ml.c5.2xlarge | $4.00 | |
ml.r5.xlarge | $4.00 | |
ml.p3.2xlarge | $4.00 | |
ml.c4.2xlarge | $4.00 | |
ml.g4dn.12xlarge | $4.00 | |
ml.m4.10xlarge | $4.00 | |
ml.c4.xlarge | $4.00 | |
ml.m5.24xlarge | $4.00 | |
ml.c5.xlarge | $4.00 | |
ml.g4dn.xlarge | $4.00 | |
ml.r5.24xlarge | $4.00 | |
ml.p2.xlarge | $4.00 | |
ml.m5.12xlarge | $4.00 | |
ml.g4dn.16xlarge | $4.00 | |
ml.p2.16xlarge | $4.00 | |
ml.c4.4xlarge | $4.00 | |
ml.r5.4xlarge | $4.00 | |
ml.c5.large | $4.00 | |
ml.m5.xlarge | $4.00 | |
ml.c5.9xlarge | $4.00 | |
ml.m4.xlarge | $4.00 | |
ml.c5.4xlarge | $4.00 | |
ml.p3.8xlarge | $4.00 | |
ml.c4.large | $4.00 | |
ml.m5.large Vendor Recommended | $4.00 | |
ml.c4.8xlarge | $4.00 | |
ml.p2.8xlarge | $4.00 | |
ml.g4dn.8xlarge | $4.00 | |
ml.t2.xlarge | $4.00 | |
ml.c5.18xlarge | $4.00 | |
ml.t2.large | $4.00 | |
ml.r5.2xlarge | $4.00 | |
ml.t2.medium | $4.00 | |
ml.t2.2xlarge | $4.00 |
Usage Information
Fulfillment Methods
Amazon SageMaker
Input:
Following are the mandatory inputs for predictions made by the algorithm:
pdffile : This is the path of the pdf file stored in S3.
Supported content types for input: application/pdf
Output
Supported content types: text/plain
Sample Output:
The Predicted Document-Type is Broker Submission Document
Invoking endpoint:
If you are using real time inferencing, please create the endpoint first and then use the following command to invoke it:
aws sagemaker-runtime invoke-endpoint --endpoint-name "endpoint-name" --body fileb://input.pdf --content-type application/pdf --accept text/plain output.out
Substitute the following parameters:
"endpoint-name" - name of the inference endpoint where the model is deployed
"input.pdf" - input pdf to do the inference on
"application/pdf"- MIME type of the given input file (above)
"output.txt" - filename where the inference results are written to.
Resources:
Link to Instructions Notebook: https://tinyurl.com/v7z73yr
Link to Sample Input Pdfs: https://tinyurl.com/y4l3muky
Link to Sample Output: https://tinyurl.com/sk3z8yx
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
Mphasis DeepInsights Document Classifier
For any assistance reach out to us at:
AWS Infrastructure
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Learn MoreRefund Policy
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