Practical AI
Low code, no code, accelerated code, & failing code
Feb 23, 2021 · 48 min · Episode 123 · 46.5 MB
0:00-48:21
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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:
Show Notes:
- Follow up content from Rajiv Shah:
- Lambda Lab’s GPU benchmarks
- Machine Learning in Microsoft Excel
- Deep Learning at the Speed of Light
- MLCommons and MLCube:
- Learning Resources:
Upcoming Events:
- Register for upcoming webinars here!
Changelog++
changelog.comThe Brave Browser
brave.comBasic Attention Token
basicattentiontoken.orgchangelog.com
changelog.comFastly
fastly.comLinode
linode.comWebsite
chrisbenson.comGitHub
github.comLinkedIn
linkedin.comX
x.comWebsite
datadan.ioGitHub
github.comX
x.comRunning code and failing models
datarobot.comRajiv’s previous episode
changelog.comLambda Lab’s GPU benchmarks
lambdalabs.comMachine Learning in Microsoft Excel
venturebeat.comDeep Learning at the Speed of Light
spectrum.ieee.orgPrevious episode about MLCommons
changelog.comMLCube project
github.comYann LeCun’s Deep Learning Course Is Now Free & Fully Online
analyticsindiamag.comTensorFlow Everywhere
tensorflow.orgupcoming webinars here
practicalai.fm