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.
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Mphasis HyperGraf Big 5 Trait Analyzer
By:
Latest Version:
4.1
Lexicon based NLP solution for predicting big 5 (OCEAN) personality traits and assigning trait scores to users.
Product Overview
The Big 5 personality analyser takes input text from a user and assigns score on the Big 5 personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism). The underlying algorithm utilises Natural Language Processing and computational psycho-linguistics to assign the scores.
Key Data
Version
By
Type
Model Package
Highlights
The solution provides assessment of an individual's score on the Big 5 (OCEAN) personality traits. The algorithm analyses individual expressions in blogs, emails, chat transcripts, tweets, Facebook posts, comments made on social media platforms etc. and conducts a lexicon-based analysis to arrive at the 5 scores.
The solution provides a way to leverage information about personality traits to provide hyper personalized experiences to individuals interacting with firms in various capacities. For instance, as a customer seeking products, or a prospective employee applying for a job, or as existing employees exploring training for improving personal effectiveness.
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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.xlarge
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$0.23/host/hr
running on ml.m5.xlarge
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 Vendor Recommended | $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 | $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
Model input and output details
Input
Summary
The algorithm works with any text data which could be in the form of a blogs, email, chat transcript, Facebook post, tweets, or any other text expression by the individual whose personality is being assessed.
The input must be in ‘.csv’ format.
The column containing the text data must be given the heading as “Text”
All the text data should contain atleast 200 words.,for better results one can provide more words.
Input MIME type
text/csv, text/plainSample input data
Output
Summary
- Output will give score to each personality trait between 1 to 5 depending on text data given as input.
- Score of 1 denotes that the person is very low on that personality trait whereas a score of 5 denotes that the person is very high on that personality trait.
- Output is in the form of a ‘.csv’ file.
Output MIME type
text/csv, text/plainSample output data
Sample notebook
Additional Resources
End User License Agreement
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Support Information
Mphasis HyperGraf Big 5 Trait Analyzer
For any assistance, please reach out at:
AWS Infrastructure
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