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.
Remote Control Reviews Aspect Detection
By:
Latest Version:
2.2
This is a Natural Language Processing based solution which can detect up to 4 aspects from online product reviews for remote control.
Product Overview
This solution identifies the various aspects from online product reviews for remote control. The following 4 aspects are identified: distance/range, battery, installation & use, and price. This enables companies to easily identify which aspects are being reviewed. This information can be used to assess changes in consumer priorities and focus on trending aspects related to remote control. Companies can use this solution for providing inputs to advertising and marketing campaigns and product design.
Key Data
Version
By
Type
Model Package
Highlights
This solution is trained on a large publicly available dataset of remote control reviews. Solution uses semi-supervised latent dirichlet allocation algorithm to learn the important keywords for 4 aspects related to remote control. Aspects for new reviews are inferred on the basis of comparison of words in the reviews with the model-learnt set of words for each aspect.
This solution can be used by e-commerce companies, manufacturers, and retailers to identify the aspects from online customer reviews.
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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.
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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
Each text file should have 1 review with maximum of 2000 characters. Should have only ASCII characters. Works only for English language inputs.
Input MIME type
text/plainSample input data
Output
Summary
Model identifies the below mentioned aspects and their respective probabilities in each sentence in a review.
- distance/range
- battery
- price
- Installation and Use
Output MIME type
text/plain, application/jsonSample 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
Remote Control Reviews Aspect Detection
For any assistance reach out to us at:
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