This full connected has it all: news, updates on AI/ML tooling, discussions about AI workflow, and learning resources. Chris and Daniel breakdown the various roles to be played in AI development including scoping out a solution, finding AI value, experimentation, and more technical engineering tasks. They also point out some good resources for exploring bias in your data/model and monitoring for fairness.

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Featuring:

Chris Benson – Twitter, GitHub, LinkedIn, Website
Daniel Whitenack – Twitter, GitHub, Website

Show Notes:

Streamlit:

Streamlit funding announcement
Previous Practical AI episode about Streamlit

GPU acceleration in Windows Subsystem for Linux

Fairness and bias:

Google’s explanation of bias in their ML crash course
IBM fairness 360
Google’s responsible AI practices
Driven Data’s Deon project
Previous Practical AI episode about bias in AI and hiring
US Department of Defense Ethical principles for AI

Chris’s personal, COVID-related blog post

Something missing or broken? PRs welcome!

Roles to play in the AI dev workflow 50:25 Share

Practical AI: Machine Learning, Data Science, LLM

Shownotes Transcript

Roles to play in the AI dev workflow