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A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

Released Tuesday, 30th March 2021
Good episode? Give it some love!
A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

Tuesday, 30th March 2021
Good episode? Give it some love!
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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://www.radekosmulski.com

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:

Radek's Book "Meta-Learning"

Andrew Ng ML Coursera

Fast AI

Universal Language Model Fine-tuning for Text Classification

How to do Machine Learning Efficiently

NPR - Two Heartbeats a Minute

Earth Species Project

A Guide to the Good Life

The Origin of Wealth

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