This podcast helps Machine Learning Engineers become the best at what they do. Join host Charlie You every week as he talks to the brightest minds in data science, artificial intelligence, and software engineering to discover how they bring cutting edge research out of the lab and into products that people love. You'll learn the skills, tools, and best practices you can use to build better ML systems and accelerate your career in this flourishing new field.
Shreya Shankar: Lessons learned after a year of putting ML into production
Shreya discusses what she's learned in the past year about making ML useful by putting into production. She touches on strategies for ensuring reproducibility, feature engineering best practices, and her checklist for building AI-driven systems.
Josh Tobin: Research at OpenAI, Full Stack Deep Learning, ML in Production
Josh discusses his research in ML for robotics at OpenAI, why putting ML into production is so hard, and how he things ML systems will be built in the future.
Sanyam Bhutani: Chai Time Data Science
Sanyam talks about teaching himself ML during college, blogging, creating the Chai Time Data Science Show, and working at H2O.ai
Devon Bernard: "If you can sell it, I can build it"
Devon talks about how he built an app that blew up to over 500k users, best practices for engineering and consulting, and startup mega-trends.
Catherine Yeo: Fairness in AI and Algorithms
Catherine Yeo discusses AI and algorithmic fairness—what it is, why it matters, and how we can work to reduce biases in our own models.
Charles Yang: Machine Learning for Scientific Research
Charles discusses the breakthrough results ML has produced in scientific research, how both traditional scientists and ML researchers can get involved, and gives an unexpected answer to a rapid fire question.
Customer ReviewsSee All
Charlie You is a great ML engineer
And a great podcast host!