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|a Chowdhury, Rumman
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| 245 |
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|a AI Superstream
|b Responsible AI
|c Chowdhury, Rumman
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| 250 |
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|a 1st edition
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| 260 |
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|a [Erscheinungsort nicht ermittelbar], Boston, MA
|b O'Reilly Media, Inc., Safari
|c 2021
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| 300 |
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|a 1 video file, circa 3 hr., 39 min.
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|a Internet videos / fast
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|a Vidéos sur Internet
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|a Streaming video / fast
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|a Vidéo en continu
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|a streaming video / aat
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|a Streaming video / http://id.loc.gov/authorities/subjects/sh2005005237
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| 653 |
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|a Internet videos / http://id.loc.gov/authorities/subjects/sh2007001612
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|a Nielsen, Aileen
|e VerfasserIn
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|a Gandhi, Triveni
|e VerfasserIn
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|a Hall, Patrick
|e VerfasserIn
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|a Online resource; Title from title screen (viewed June 16, 2021)
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|u https://learning.oreilly.com/videos/~/0636920586517/?ar
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|a Join us for an event focused on the many aspects of designing, deploying, and maintaining responsible AI. Event chair and responsible AI expert Rumman Chowdhury offers overarching context, stitching together shorter tech talks and conversations with industry leaders. What you'll learn and how you can apply it Discover what responsible AI includes (and what it doesn't) See what responsible AI looks like in action, from data to deployment to debugging Learn how to debug your ML model Explore real-world applications of responsible AI Understand what industry leaders think about when they think about responsibility This course is for you because ... You're a machine learning engineer or data scientist interested in responsible AI. You're engaged in conversations about ethics and AI. You're wondering how to improve your own AI and machine learning. You're responsible for implementing fair or ethical AI practices in your role or project and looking for hands-on examples. Recommended follow-up: Read Responsible Machine Learning (report) Read AI and the Law (report) Read Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (book)
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