Adam Scott on ethical web development
The O’Reilly Programming Podcast: Building applications that work everywhere for everyone.
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Martin Charlier explores a new technique to apply in your prototyping work.
Building distributed systems with containers
Five questions for Brendan Burns: How containers and cluster management have changed systems development, and common patterns for building distributed systems.
Big data’s biggest secret: Hyperparameter tuning
The toughest part of machine learning with Spark isn't what you think it is.
The community lab: A student’s door to opportunity
Shreya Thiagarajan describes the invaluable experience she gained while working in a local community lab.
Collaboration and the designer’s mindset
A look at real-world instances where design collaboration has achieved excellent results.
Management tips for a thriving team
Five questions for VM Brasseur and Deb Nicholson: How to overcome communication challenges and encourage collaborative work when managing globally distributed teams.
Three enablers for machine learning in data unification: Trust, legacy, and scale
Human-guided ML pipelines for data unification and cleaning might be the only way to provide complete and trustworthy data sets for effective analytics.
Julie Stanford on vetting designs through rapid experimentation
The O’Reilly Design Podcast: Quickly test ideas like a design thinker.
Jack Daniel on building community and historical context in InfoSec
The O'Reilly Security Podcast: The role of community, the proliferation of BSides and other InfoSec community events, and celebrating our heroes and heroines.
Contouring learning rate to optimize neural nets
Tips and tricks for treating learning rate as a hyperparameter, and using visualizations to see what’s really going on.
Creating better disaster recovery plans
Five questions for Tanya Reilly: How service interdependencies make recovery harder and why it’s a good idea to deliberately and preemptively manage dependencies.