Machine learning and data science are full of best practices and important workflows. Can we extrapolate these to our broader lives? Eugene Yan and I give it a shot on this slightly more philosophical episode of Talk Python To Me.
The seven lessons:
1. Data cleaning: Assess what you consume
2. Low vs. high signal data: Seek to disconfirm and update
3. Explore-Exploit: Balance for greater long-term reward
4. Transfer Learning: Books and papers are cheat codes
5. Iterations: Find reps you can tolerate, and iterate fast
6. Overfitting: Focus on intuition and keep learning
7. Ensembling: Diversity is strength
Links from the showEugene Yan: @eugeneyan
What Machine Learning Can Teach Us About Life - 7 Lessons article: eugeneyan.com
Maker's schedule vs. manager's schedule: paulgraham.com
Naval Podcast: overcast.fm
How to Write Better with The Why, What, How Framework https://eugeneyan.com/writing/writing-docs-why-what-how/
Resources mentioned towards the end of the podcast: eugeneyan.com/resources
New media example - Metal song decomposed by classical musicians
Opera singer: youtube.com
Composer music: youtube.com
YouTube Live Stream: youtube.com
PyCon Ticket Giveaway: talkpython.fm/pycon2021
SponsorsRetool
Linode
Talk Python Training