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

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 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!

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Creators & Guests

Host

Chris Benson

Host

Daniel Whitenack

What is Practical AI?

Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more).

The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!