amazon-sagemaker-modeldb-sync | simple event-based architecture | Data Labeling library

 by   aws-samples Python Version: Current License: Non-SPDX

kandi X-RAY | amazon-sagemaker-modeldb-sync Summary

kandi X-RAY | amazon-sagemaker-modeldb-sync Summary

amazon-sagemaker-modeldb-sync is a Python library typically used in Artificial Intelligence, Data Labeling applications. amazon-sagemaker-modeldb-sync has no bugs, it has no vulnerabilities and it has low support. However amazon-sagemaker-modeldb-sync build file is not available and it has a Non-SPDX License. You can download it from GitHub.

This sample deploys a simple event-based architecture to synchronize SageMaker model metadata to ModelDB with the ModelDB Light API. The synchronization will be triggered when SageMaker Training Jobs complete. A Step Function will be executed to validate certain tags that are applied to training jobs, gather details about the trained model, and synchronize those details to a ModelDB instance using the ModelDB Light API. This solution can be extended to synchronize any data that's supported by the Light API, or used as a pattern for synchronizing to other model metadata management systems.
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              amazon-sagemaker-modeldb-sync has a low active ecosystem.
              It has 4 star(s) with 3 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              amazon-sagemaker-modeldb-sync has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of amazon-sagemaker-modeldb-sync is current.

            kandi-Quality Quality

              amazon-sagemaker-modeldb-sync has no bugs reported.

            kandi-Security Security

              amazon-sagemaker-modeldb-sync has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              amazon-sagemaker-modeldb-sync has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

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              amazon-sagemaker-modeldb-sync releases are not available. You will need to build from source code and install.
              amazon-sagemaker-modeldb-sync has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed amazon-sagemaker-modeldb-sync and discovered the below as its top functions. This is intended to give you an instant insight into amazon-sagemaker-modeldb-sync implemented functionality, and help decide if they suit your requirements.
            • A lambda function
            • Syncs model to modeldb
            • Validates the existence of the tags in training job
            • Return the tag value for a given tagName
            Get all kandi verified functions for this library.

            amazon-sagemaker-modeldb-sync Key Features

            No Key Features are available at this moment for amazon-sagemaker-modeldb-sync.

            amazon-sagemaker-modeldb-sync Examples and Code Snippets

            No Code Snippets are available at this moment for amazon-sagemaker-modeldb-sync.

            Community Discussions

            QUESTION

            How can I do this split process in Python?
            Asked 2021-Dec-30 at 14:06

            I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

            What I've done so far is make this representation with the same enumerator class.

            A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

            ...

            ANSWER

            Answered 2021-Dec-30 at 13:57

            Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

            Source https://stackoverflow.com/questions/70532286

            QUESTION

            Replacing a character with a space and dividing the string into two words in R
            Asked 2020-Nov-18 at 07:32

            I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

            In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

            i have this:

            ...

            ANSWER

            Answered 2020-Nov-16 at 07:24

            QUESTION

            Azure ML FileDataset registers, but cannot be accessed for Data Labeling project
            Asked 2020-Oct-28 at 20:31

            Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

            Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

            Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

            ...

            ANSWER

            Answered 2020-Oct-27 at 22:39

            Is the data behind virtual network by any chance?

            Source https://stackoverflow.com/questions/64546521

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install amazon-sagemaker-modeldb-sync

            You can download it from GitHub.
            You can use amazon-sagemaker-modeldb-sync like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            git@github.com:aws-samples/amazon-sagemaker-modeldb-sync.git

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