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    DeepInsights Text N-gram Analyser

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    Sold by: Mphasis 
    Deployed on AWS
    This NLP based solution finds meaningful and frequent n-grams/phrases of words in the provided text.

    Overview

    Text n-gram analyser finds meaningful and frequent n-grams in the provided text. An n-gram is a contiguous sequence of n terms from a given sample of text. Currently, this module provides bigrams, trigrams and four-grams with their corresponding number of frequent occurrences in the text. These meaningful n-grams are handy in various linguistic analysis solutions such as entity identification, document indexing, and topic modelling.

    Highlights

    • Extracted n-grams can be applied for next word predictions and spelling error corrections.
    • Helps in entity identification, document indexing, and topic modelling.
    • Mphasis DeepInsights is a cloud-based cognitive computing platform that offers data extraction & predictive analytics capabilities. Need Customized Deep learning and Machine Learning Solutions? Get in Touch!

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Pricing

    DeepInsights Text N-gram Analyser

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    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.

    Usage costs (52)

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    Dimension
    Description
    Cost/host/hour
    ml.m5.large Inference (Batch)
    Recommended
    Model inference on the ml.m5.large instance type, batch mode
    $8.00
    ml.m5.large Inference (Real-Time)
    Recommended
    Model inference on the ml.m5.large instance type, real-time mode
    $4.00
    ml.m4.4xlarge Inference (Batch)
    Model inference on the ml.m4.4xlarge instance type, batch mode
    $8.00
    ml.m5.4xlarge Inference (Batch)
    Model inference on the ml.m5.4xlarge instance type, batch mode
    $8.00
    ml.m4.16xlarge Inference (Batch)
    Model inference on the ml.m4.16xlarge instance type, batch mode
    $8.00
    ml.m5.2xlarge Inference (Batch)
    Model inference on the ml.m5.2xlarge instance type, batch mode
    $8.00
    ml.p3.16xlarge Inference (Batch)
    Model inference on the ml.p3.16xlarge instance type, batch mode
    $8.00
    ml.m4.2xlarge Inference (Batch)
    Model inference on the ml.m4.2xlarge instance type, batch mode
    $8.00
    ml.c5.2xlarge Inference (Batch)
    Model inference on the ml.c5.2xlarge instance type, batch mode
    $8.00
    ml.p3.2xlarge Inference (Batch)
    Model inference on the ml.p3.2xlarge instance type, batch mode
    $8.00

    Vendor refund policy

    Currently we do not support refunds, but you can cancel your subscription to the service at any time.

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    Usage information

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    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:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    Bug fixes and uppdates

    Additional details

    Inputs

    Summary
    • Sample input file: India’s highest award for lifetime achievement in sports is named after the hockey wizard – Dhyan Chand Award.
    • The input file is in with “utf-8” encoding
    • The text should be written in English language
    • The size of input text file should be less than 200 KB
    Input MIME type
    text/csv, application/json, text/plain
    https://github.com/Mphasis-ML-Marketplace/DeepInsights-Text-N-gram-Analyser/tree/main/input
    https://github.com/Mphasis-ML-Marketplace/DeepInsights-Text-N-gram-Analyser/tree/main/input

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