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Charlie You에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Charlie You 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)

1:38:02
 
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Manage episode 288765085 series 2849409
Charlie You에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Charlie You 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

Make Time

You Are Here

  continue reading

32 에피소드

Artwork
icon공유
 
Manage episode 288765085 series 2849409
Charlie You에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Charlie You 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

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

Make Time

You Are Here

  continue reading

32 에피소드

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