Low code, no code, accelerated code, & failing code
Practical AI: Machine Learning, Data Science
English - February 23, 2021 16:00 - 48 minutes - 44.4 MB - ★★★★★ - 37 ratingsTechnology Education How To changelog machine learning deep learning artificial intelligence neural networks computer vision Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
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!
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 – Twitter, GitHub, LinkedIn, WebsiteDaniel Whitenack – Twitter, GitHub, Website
Show Notes:
Follow up content from Rajiv Shah:
Running code and failing models
Rajiv’s previous episode
Lambda Lab’s GPU benchmarks
Machine Learning in Microsoft Excel
Deep Learning at the Speed of Light
MLCommons and MLCube:
Previous episode about MLCommons
MLCube project
Learning Resources:
Yann LeCun’s Deep Learning Course Is Now Free & Fully Online
TensorFlow Everywhere
Something missing or broken? PRs welcome!