Roles to play in the AI dev workflow
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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!)