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.
COVID-19 News Sentiment Analyzer Free trial
By:
Latest Version:
2.0
A News Sentiment Analyzer for tracking developments around COVID-19 pandemic.
Product Overview
COVID-19 News Headlines Sentiment Analyzer helps businesses to analyze headlines around the pandemic. It helps the users to identify COVID-19 related sentiments based on analysis of news headlines and classify them as positive, negative, neutral and mixed. It determines the sentiment of News headlines by maintaining aspect and polarity associated with COVID-19. This analysis can be used in various scenarios like stock movement predictions, econometric analysis, policy effectiveness and risk analytics.
Key Data
Version
By
Type
Model Package
Highlights
Highly customized Deep Learning based model for COVID-19 news headlines analysis, trained using State of the Art Transformer model along with COVID-19 specific features augmentation. The dataset was sourced from recent news articles and custom tagged.
This solution comes with a highly accurate pre-trained model which can be used directly for sentiment analysis. We are also providing, highly customizable training module optimized and tuned for COVID-19 use cases, where new data can be fed, and model can be trained end to end.
Need customized sentiment analysis solutions? Get in touch!
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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$5.00/hr
running on ml.m5.2xlarge
Model Batch Transform$10.00/hr
running on ml.m5.2xlarge
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$0.461/host/hr
running on ml.m5.2xlarge
SageMaker Batch Transform$0.461/host/hr
running on ml.m5.2xlarge
About Free trial
Try this product for 30 days. There will be no software charges, but AWS infrastructure charges still apply. Free Trials will automatically convert to a paid subscription upon expiration.
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 | $5.00 | |
ml.m5.4xlarge | $5.00 | |
ml.m4.16xlarge | $5.00 | |
ml.m5.2xlarge Vendor Recommended | $5.00 | |
ml.p3.16xlarge | $5.00 | |
ml.m4.2xlarge | $5.00 | |
ml.c5.2xlarge | $5.00 | |
ml.p3.2xlarge | $5.00 | |
ml.c4.2xlarge | $5.00 | |
ml.m4.10xlarge | $5.00 | |
ml.c4.xlarge | $5.00 | |
ml.m5.24xlarge | $5.00 | |
ml.c5.xlarge | $5.00 | |
ml.p2.xlarge | $5.00 | |
ml.m5.12xlarge | $5.00 | |
ml.p2.16xlarge | $5.00 | |
ml.c4.4xlarge | $5.00 | |
ml.m5.xlarge | $5.00 | |
ml.c5.9xlarge | $5.00 | |
ml.m4.xlarge | $5.00 | |
ml.c5.4xlarge | $5.00 | |
ml.p3.8xlarge | $5.00 | |
ml.m5.large | $5.00 | |
ml.c4.8xlarge | $5.00 | |
ml.p2.8xlarge | $5.00 | |
ml.c5.18xlarge | $5.00 |
Usage Information
Fulfillment Methods
Amazon SageMaker
Usage Methodology for the algorithm: 1) The input has to be a .csv file with the content in a column titled 'sentence' 2) The file should follow 'utf-8' encoding. 3) The input can have a maximum of 512 words.
General instructions for consuming the service on Sagemaker: 1) Access to AWS SageMaker and the model package 2) An S3 bucket to specify input/output 3) Role for AWS SageMaker to access input/output from S3
Input
Supported content types: text/csv
SNo-|--------------------sentence-------------------------
- Artist project to combat isolation turns loneliness......
- Grieving from a distance: How COVID-19 changes......
- Dubious screenshot claims Chinese website...
- No charges after car 'cruise night' in Carievale...
- Coronavirus: charities rally to help older ...
Output
Content type: text/csv
--------------sentence-------------------------------------|- sentiment----- Artist project to combat isolation turns loneliness...... Negative Grieving from a distance: How COVID-19 changes...... Neutral Dubious screenshot claims Chinese website... Negative No charges after car 'cruise night' in Carievale... Positive Coronavirus: charities rally to help older ... Positive
Invoking endpoint
AWS CLI Command
You can invoke endpoint using AWS CLI:
aws sagemaker-runtime invoke-endpoint --endpoint-name $model_name --body fileb://$file_name --content-type 'text/csv' --region us-east-2 output.csvSubstitute the following parameters:
"model_name"- name of the inference endpoint where the model is deployedinput.csv- input file to do the inference ontext/csv- Type of input dataoutput.csv- filename where the inference results are written to
Resources
Sample Notebook : https://tinyurl.com/y964pc62 Sample Input : https://tinyurl.com/yaddn5ck Sample Output: https://tinyurl.com/y75nsmcv
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
COVID-19 News Sentiment Analyzer
For any assistance reach out to us at:
AWS Infrastructure
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Learn MoreRefund Policy
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