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\n Jobs at BOSS AI\n
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Student Initiative - Meta features extraction for image, audio, and time series

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  • \n \n Nashville, TN\n
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  • \nCategory: Interns
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  • \nType: Intern
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  • \nMin. Experience: Intern
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<div class="row">\n  <article class="col-xs-12 col-md-7">\n    <div class="job-descr content">\n      <p><b style="font-weight:normal;" id="docs-internal-guid-06a11738-7fff-297e-8932-0c205fa081d9"></b></p>\n
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1.1 Initiative Summary:

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Contribute to our new open source library Elemeta by extending it to provide image, audio, and time series features out of the box. The purpose of Elemeta is to provide a unified out-of-the-box approach for extracting information from unstructured data. By providing structured information over unstructured data, Elemeta allows practitioners to solve real life problems faster and build and monitor better machine learning models. Using this open source package, Blattner team is able to provide enterprise applications faster and make Superwise model monitoring applicable for unstructured use cases.

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1.2 Desired Outcomes

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Ideally, a pull request (one or more) should be submitted to the open source repository with a new set of meta features included. It is possible to provide such extensions only to one or more data types: Images, audio, and time series. An example of a potential features for an image would include: Resolution, Brightness, Sharpness, Is it a selfie, Does it contain profanity, Amount of objects, Indoor/Outdoor, etc.

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1.3 Core Skills Required

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Knowledgeable in software engineering, in particular how to work with Git and basic Python code standards. A machine learning orientation to understand how existing image, audio or timeseries libraries can be leveraged for enrichment.

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1.4 Estimated Effort

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The work will start by envisioning and refining the backlog of possible features to extract. Following a joint decision and prioritization, we will refine the list and decide which set of features to implement in which iteration. The work will be broken into iterations. At the end of each iteration, we will deliver a pull request to the main package branch to enrich the package.

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1.5 Additional Information

\nThis is an open source project that offers you the opportunity to join the open source community as a contributor (and you will be recognized as such in the repository). Visit here for more information about Elemeta. In this project, a core developer and data scientist of Superwise will lead and mentor the work (including code review). Superwise is a leading model observability SaaS solution in the industry.

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    \n Should be {http://www.linkedin.com/pub/[member-name/]x/y/z}\n or {http://www.linkedin.com/in/string}\n

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\n","datePosted":"2023-11-17T04:56:41.155Z","employmentType":[],"hiringOrganization":{"@type":"Organization","name":"superwise.ai","sameAs":"https://superwise.ai","logo":"https://cdn.filestackcontent.com/Ttam5s8dRjyBOUPy03Sg"},"jobLocationType":"TELECOMMUTE","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"United States"}},"applicantLocationRequirements":{"@type":"Country","name":"Earth"}}

Student Initiative - Meta features extraction for image, audio, and time series

superwise.ai

superwise.ai

United States · Remote
Posted on Friday, November 17, 2023
Apply

1.1 Initiative Summary:

Contribute to our new open source library Elemeta by extending it to provide image, audio, and time series features out of the box. The purpose of Elemeta is to provide a unified out-of-the-box approach for extracting information from unstructured data. By providing structured information over unstructured data, Elemeta allows practitioners to solve real life problems faster and build and monitor better machine learning models. Using this open source package, Blattner team is able to provide enterprise applications faster and make Superwise model monitoring applicable for unstructured use cases.


1.2 Desired Outcomes

Ideally, a pull request (one or more) should be submitted to the open source repository with a new set of meta features included. It is possible to provide such extensions only to one or more data types: Images, audio, and time series. An example of a potential features for an image would include: Resolution, Brightness, Sharpness, Is it a selfie, Does it contain profanity, Amount of objects, Indoor/Outdoor, etc.


1.3 Core Skills Required

Knowledgeable in software engineering, in particular how to work with Git and basic Python code standards. A machine learning orientation to understand how existing image, audio or timeseries libraries can be leveraged for enrichment.


1.4 Estimated Effort

The work will start by envisioning and refining the backlog of possible features to extract. Following a joint decision and prioritization, we will refine the list and decide which set of features to implement in which iteration. The work will be broken into iterations. At the end of each iteration, we will deliver a pull request to the main package branch to enrich the package.


1.5 Additional Information

This is an open source project that offers you the opportunity to join the open source community as a contributor (and you will be recognized as such in the repository). Visit here for more information about Elemeta. In this project, a core developer and data scientist of Superwise will lead and mentor the work (including code review). Superwise is a leading model observability SaaS solution in the industry.

  • Should be {http://www.linkedin.com/pub/[member-name/]x/y/z} or {http://www.linkedin.com/in/string}

Apply now
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