Roles to play in the AI dev workflow
Practical AI: Machine Learning, Data Science
English - June 22, 2020 19:45 - 50 minutes - 46.3 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
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.
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, WebsiteDaniel 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!