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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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Ball Bearings Quality Inspection

By:
Persistent Systems
Latest Version:
0.1
Classifies the Ball Bearings as good or defective
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    Product Overview

    A bearing is a machine element that constrains relative motion to only the desired motion, and reduces friction between moving parts. There are many types of bearings, each used for different purposes such as ball bearings, roller bearings, ball thrust bearings, roller thrust bearings and tapered roller thrust bearings. Usually, bearings manufacturing process requires a human inspection of the quality of bearings which is time-consuming process. Moreover, a manual repetitive inspection task may result in inconsistencies over a period of time.

    Key Data

    Version
    0.1
    Usage Instructions
    Release Notes
    By
    Persistent Systems
    Categories
    Classification-Image
    Industrial IoT
    Type
    Model Package
    Fulfillment Methods
    Amazon SageMaker

    Highlights

    • A binary classifier trained using convolutional neural network (CNN) that processes the Ball Bearings images and classifies them as good or defective

    • Trained using SageMaker default Image Classification algorithm

    • An edge ML based solution can be extended using this model with an IP camera installed on manufacturing assembly line

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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.


    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$0.00/hr

    running on ml.m4.xlarge

    Model Batch Transform$0.00/hr

    running on ml.m4.xlarge

    Infrastructure 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$0.24/host/hr

    running on ml.m4.xlarge

    SageMaker Batch Transform$0.24/host/hr

    running on ml.m4.xlarge

    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.xlarge
    Vendor Recommended
    $0.00

    Usage Information

    Fulfillment Methods

    Amazon SageMaker

    Download the Jupyter notebook in "Additional Resources" section and follow readme.txt provided.

    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

    AWS Infrastructure

    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.

    Learn More

    Refund Policy

    Since you are not being charged currently for the use of this software there will be no refund of any charges.

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