Sold by: MphasisÂ
Deployed on AWS
Lexicon based NLP Solution analyses employee reviews to assess which cultural values are being mentioned.
Overview
Corporate culture defined as "a set of norms and values that are widely shared and strongly held throughout the organization" is an important aspect of employees’ relationship with their organization. The most important corporate cultural categories are: Integrity, Teamwork, Innovation, Respect, Quality, Safety, Community, Communication, and Reward. This solution identifies which of these 9 values find mention in employee reviews. This enables organizations to assess whether the values they espouse are currently experienced by their employees in the workplace, and track changes in corporate values over time.
Highlights
- The solution helps organizations to measure the pulse of their employees, It helps organizations ascertain whether their standards for corporate values are reflected in actual experience of employees and informs them as to whether the cultural values remain committed to paper or are disseminated in the work force. This also helps in identifying lagging or falling values and enable organizations to take focused incentives and internal marketing efforts to address specific areas of concern. This in turn would improve the efficiency of the organization’s employee engagement efforts
- This solution can be applied across industries for internal marketing, improving employee satisfaction, targeted initiatives for employee engagement, and values based strategic planning.
- Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need customized Machine Learning and Deep Learning solutions? Get in touch!
Details
Sold by
Delivery method
Latest version
Deployed on AWS
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Features and programs
Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.m5.large Inference (Batch) Recommended | Model inference on the ml.m5.large instance type, batch mode | $16.00 |
ml.m5.large Inference (Real-Time) Recommended | Model inference on the ml.m5.large instance type, real-time mode | $8.00 |
ml.m4.4xlarge Inference (Batch) | Model inference on the ml.m4.4xlarge instance type, batch mode | $16.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $16.00 |
ml.m4.16xlarge Inference (Batch) | Model inference on the ml.m4.16xlarge instance type, batch mode | $16.00 |
ml.m5.2xlarge Inference (Batch) | Model inference on the ml.m5.2xlarge instance type, batch mode | $16.00 |
ml.p3.16xlarge Inference (Batch) | Model inference on the ml.p3.16xlarge instance type, batch mode | $16.00 |
ml.m4.2xlarge Inference (Batch) | Model inference on the ml.m4.2xlarge instance type, batch mode | $16.00 |
ml.c5.2xlarge Inference (Batch) | Model inference on the ml.c5.2xlarge instance type, batch mode | $16.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $16.00 |
Vendor refund policy
Currently we do not support refunds, but you can cancel your subscription to the service at any time.
Legal
Vendor terms and conditions
Upon subscribing to this product, you must acknowledge and agree to the terms and conditions outlined in the vendor's End User License Agreement (EULA)Â .
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Bug Fixes and Performance Improvement
Additional details
Inputs
- Summary
Amazon SageMaker
Input
• Supported content types: text/csv • Sample input file: (https://tinyurl.com/y42hr3bg ) • The input can be provided as (.csv) file and with 'utf-8' encoding • The input file should contain only a single column heading as 'Reviews', with different rows containing different reviews •The solution currently handles only English language reviews with a maximum of reviews 9000 per request (~800kb)
Output
• Content type: text/csv • Output file will contain the original 'Reviews' column along with various cultural category columns • Each of the cultural category column can have values either 'Yes' or 'No' • Sample output file: (https://tinyurl.com/yyln5ehv )
Invoking endpoint
AWS CLI Command
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://cultural_categ_input.csv --content-type text/csv --accept application/cultural_categ_output.csvSubstitute the following parameters:
- "endpoint-name" - name of the inference endpoint where the model is deployed
- cultural_categ_input.csv - input csv file to do the inference on
- text/csv - type of the given input text file
- cultural_categ_output.csv - filename where the inference results are written to
Resources
• [Cultural category sample data] (https://tinyurl.com/y42hr3bg ) • [Sample Notebook] (https://tinyurl.com/y3amtsrp )
- Input MIME type
- text/csv
See Input Summary
See Input Summary
Resources
Vendor resources
Support
Vendor support
For any assistance, please reach out at:
AWS infrastructure support
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.
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