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Timestamps: (03:00) How did I get exposed to computer science and what made me pursue it? (10:00) Why machine learning? (15:10) How did I learn ML? How would I recommend someone do it today? (27:00) Why start this podcast? What is the goal? (29:40) Rapid-fire questions

Links:  https://www.notion.so/charlieyou/Content-Pipeline-af923f8b990646369a85a00a348a1e12 (Marc Andreeson: Software is eating the world)  https://breakingsmart.com/en/season-1/ (Breaking Smart)  https://www.coursera.org/learn/machine-learning (Andrew Ng's ML course)  https://www.deeplearning.ai/ (deeplearning.ai)  http://web.stanford.edu/class/cs224n/ (Stanford CS224n)  http://cs231n.stanford.edu/ (Stanford CS231n)  https://vark-learn.com/ (VARK Learning Styles)  https://www.deeplearningbook.org/ (Deep Learning textbook)  https://course.fast.ai/ (FastAI Practical Deep Learning for Coders)  https://nav.al/ (Naval Podcast)  https://www.swyx.io/writing/learn-in-public/ (swyx: Learn in Public)  https://podcastclub.link/ (Seth Godin Akimbo Podcast Workshop)  https://www.amazon.com/Meditations-New-Translation-Marcus-Aurelius/dp/0812968255 (Marcus Aurelius: Meditations)  https://www.amazon.com/ONE-Thing-Surprisingly-Extraordinary-Results/dp/1885167776/ (The ONE Thing)