Low code, no code, accelerated code, & failing code

Low code, no code, accelerated code, & failing code

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124 of 354
Czas
48min
Język
Angielski
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Kategoria
Literatura Faktu

In this Fully-Connected episode, Chris and Daniel discuss low code / no code development, GPU jargon, plus more data leakage issues. They also share some really cool new learning opportunities for leveling up your AI/ML game!

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Featuring:

• Chris Benson – Website • , GitHub • , LinkedIn • , X • Daniel Whitenack – Website • , GitHub • , X Show Notes:

• Follow up content from Rajiv Shah: Running code and failing modelsRajiv’s previous episodeLambda Lab’s GPU benchmarksMachine Learning in Microsoft ExcelDeep Learning at the Speed of Light • MLCommons and MLCube: Previous episode about MLCommonsMLCube project • Learning Resources: Yann LeCun’s Deep Learning Course Is Now Free & Fully OnlineTensorFlow Everywhere Upcoming Events:

• Register for upcoming webinars here • !


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