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A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)
Manage episode 288765085 series 2849409
Radek Osmulski is a fully self-taught machine learning engineer. After getting tired of his corporate job, he taught himself programming and started a new career as a Ruby on Rails developer. He then set out to learn machine learning. Since then, he's been a Fast AI International Fellow, become a Kaggle Master, and is now an AI Data Engineer on the Earth Species Project.
Learn more about Radek:
https://twitter.com/radekosmulski
Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: http://cyou.ai/newsletter
Follow Charlie on Twitter: https://twitter.com/CharlieYouAI
Subscribe to ML Engineered: https://mlengineered.com/listen
Comments? Questions? Submit them here: http://bit.ly/mle-survey
Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/
Timestamps:
02:15 How Radek got interested in programming and computer science
09:00 How Radek taught himself machine learning
26:40 The skills Radek learned from Fast AI
39:20 Radek's recommendations for people learning ML now
51:30 Why Radek is writing a book
01:01:20 Radek's work at the Earth Species Project
01:10:15 How the ESP collects animal language data
01:21:05 Rapid fire questions
Links:
Universal Language Model Fine-tuning for Text Classification
32 에피소드
Manage episode 288765085 series 2849409
Radek Osmulski is a fully self-taught machine learning engineer. After getting tired of his corporate job, he taught himself programming and started a new career as a Ruby on Rails developer. He then set out to learn machine learning. Since then, he's been a Fast AI International Fellow, become a Kaggle Master, and is now an AI Data Engineer on the Earth Species Project.
Learn more about Radek:
https://twitter.com/radekosmulski
Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: http://cyou.ai/newsletter
Follow Charlie on Twitter: https://twitter.com/CharlieYouAI
Subscribe to ML Engineered: https://mlengineered.com/listen
Comments? Questions? Submit them here: http://bit.ly/mle-survey
Take the Giving What We Can Pledge: https://www.givingwhatwecan.org/
Timestamps:
02:15 How Radek got interested in programming and computer science
09:00 How Radek taught himself machine learning
26:40 The skills Radek learned from Fast AI
39:20 Radek's recommendations for people learning ML now
51:30 Why Radek is writing a book
01:01:20 Radek's work at the Earth Species Project
01:10:15 How the ESP collects animal language data
01:21:05 Rapid fire questions
Links:
Universal Language Model Fine-tuning for Text Classification
32 에피소드
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