Radek Osmulski's guest appearances

Radek Osmulski

Chai Time Data Science 

Machine Learning Engineered

Sara Hooker

Ines Montani

Judy Gichoya

Rachel Thomas

Anthony Goldbloom

Andrew Shaw

Richard Craib

John Miller

Ian Ozsvald

Michael Kennedy

Bryan Catanzaro

Jose Fernandez

Marios Michailidis

Samuel Castro

Arno Candel

OwlTail

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.comhttps://twitter.com/radekosmulskiEvery 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/newsletterFollow Charlie on Twitter: https://twitter.com/CharlieYouAISubscribe to ML Engineered: https://mlengineered.com/listenComments? Questions? Submit them here: http://bit.ly/mle-surveyTake the Giving What We Can Pledge: https://www.givingwhatwecan.org/Timestamps:02:15 How Radek got interested in programming and computer science09:00 How Radek taught himself machine learning26:40 The skills Radek learned from Fast AI39:20 Radek's recommendations for people learning ML now51:30 Why Radek is writing a book01:01:20 Radek's work at the Earth Species Project01:10:15 How the ESP collects animal language data01:21:05 Rapid fire questionsLinks:Radek's Book "Meta-Learning"Andrew Ng ML CourseraFast AIUniversal Language Model Fine-tuning for Text ClassificationHow to do Machine Learning EfficientlyNPR - Two Heartbeats a MinuteEarth Species ProjectA Guide to the Good LifeThe Origin of WealthMake TimeYou Are Here

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:<a href="https://www.radekosmulski.com" rel="noopener noreferrer nofollow" target="_blank">https://www.radekosmulski.com</a><a href="https://twitter.com/radekosmulski" rel="noopener noreferrer nofollow" target="_blank">https://twitter.com/radekosmulski</a>Every Thursday I send out the most useful things I’ve learned, curated specifically for the busy machine learning engineer. Sign up here: <a href="http://cyou.ai/newsletter" rel="noopener noreferrer nofollow" target="_blank">http://cyou.ai/newsletter</a>Follow Charlie on Twitter: <a href="https://twitter.com/CharlieYouAI" rel="noopener noreferrer nofollow" target="_blank">https://twitter.com/CharlieYouAI</a>Subscribe to ML Engineered: <a href="https://mlengineered.com/listen" rel="noopener noreferrer nofollow" target="_blank">https://mlengineered.com/listen</a>Comments? Questions? Submit them here: <a href="http://bit.ly/mle-survey" rel="noopener noreferrer nofollow" target="_blank">http://bit.ly/mle-survey</a>Take the Giving What We Can Pledge: <a href="https://www.givingwhatwecan.org/" rel="noopener noreferrer nofollow" target="_blank">https://www.givingwhatwecan.org/</a> Timestamps:02:15 How Radek got interested in programming and computer science09:00 How Radek taught himself machine learning26:40 The skills Radek learned from Fast AI39:20 Radek's recommendations for people learning ML now51:30 Why Radek is writing a book01:01:20 Radek's work at the Earth Species Project01:10:15 How the ESP collects animal language data01:21:05 Rapid fire questions Links:<a href="https://gumroad.com/l/learn_deep_learning" rel="noopener noreferrer nofollow" target="_blank">Radek's Book "Meta-Learning"</a><a href="https://www.coursera.org/learn/machine-learning" rel="noopener noreferrer nofollow" target="_blank">Andrew Ng ML Coursera</a><a href="https://www.fast.ai" rel="noopener noreferrer nofollow" target="_blank">Fast AI</a><a href="https://arxiv.org/abs/1801.06146" rel="noopener noreferrer nofollow" target="_blank">Universal Language Model Fine-tuning for Text Classification</a><a href="https://www.kdnuggets.com/2018/03/machine-learning-efficiently.html" rel="noopener noreferrer nofollow" target="_blank">How to do Machine Learning Efficiently</a><a href="https://www.npr.org/2020/02/25/809336135/two-heartbeats-a-minute" rel="noopener noreferrer nofollow" target="_blank">NPR - Two Heartbeats a Minute</a><a href="https://www.earthspecies.org/" rel="noopener noreferrer nofollow" target="_blank">Earth Species Project</a><a href="https://www.goodreads.com/book/show/5617966-a-guide-to-the-good-life" rel="noopener noreferrer nofollow" target="_blank">A Guide to the Good Life</a><a href="https://store.hbr.org/product/the-origin-of-wealth-evolution-complexity-and-the-radical-remaking-of-economics/777X" rel="noopener noreferrer nofollow" target="_blank">The Origin of Wealth</a><a href="https://maketime.blog" rel="noopener noreferrer nofollow" target="_blank">Make Time</a><a href="https://plumvillage.org/books/you-are-here/" rel="noopener noreferrer nofollow" target="_blank">You Are Here</a>

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

Video version available here: https://youtu.be/4h41v07bYYI Subscribe here to the newsletter: https://tinyletter.com/sanyambhutani In this episode, Sanyam Bhutani interviews a machine learning hero to the complete fast.ai: Radek Osmulski. Personal Note: I think this is one of the most honest, and the best interviews in terms of the transparent Kaggle, learning to learn, and how to approach machine learning problems or machine learning materials advice. Radek shares his journey with complete honesty about how he went about learning the fast.ai materials, how he went on to smashing the kaggle competitions that he participated in, and his journey on learning to learn about all of the materials fast.ai and beyond in the machine learning world. They also talk a lot about learning to learn fast ai, and Kaggle all three together and individually as well. Follow: Radek: https://twitter.com/radekosmulski https://medium.com/@radekosmulski https://www.kaggle.com/radek1 https://www.linkedin.com/in/radek-osmulski-6b935794/?originalSubdomain=pl Sanyam Bhutani: https://twitter.com/bhutanisanyam1 About: http://chaitimedatascience.com/ A show for Interviews with Practitioners, Kagglers &amp; Researchers and all things Data Science hosted by Sanyam Bhutani. You can expect weekly episodes every Sunday, Thursday available as Video, Podcast, and blogposts. If you'd like to support the podcast: https://www.patreon.com/chaitimedatascience Intro track: Flow by LiQWYD https://soundcloud.com/liqwyd

Video version available here: <a href="https://youtu.be/4h41v07bYYI" rel="nofollow" target="_blank">https://youtu.be/4h41v07bYYI</a> Subscribe here to the newsletter: <a href="https://tinyletter.com/sanyambhutani" rel="nofollow" target="_blank">https://tinyletter.com/sanyambhutani</a> In this episode, Sanyam Bhutani interviews a machine learning hero to the complete <a href="http://fast.ai" rel="nofollow" target="_blank">fast.ai</a>: Radek Osmulski. Personal Note: I think this is one of the most honest, and the best interviews in terms of the transparent Kaggle, learning to learn, and how to approach machine learning problems or machine learning materials advice. Radek shares his journey with complete honesty about how he went about learning the <a href="http://fast.ai" rel="nofollow" target="_blank">fast.ai</a> materials, how he went on to smashing the kaggle competitions that he participated in, and his journey on learning to learn about all of the materials <a href="http://fast.ai" rel="nofollow" target="_blank">fast.ai</a> and beyond in the machine learning world. They also talk a lot about learning to learn fast ai, and Kaggle all three together and individually as well. Follow: Radek: <a href="https://twitter.com/radekosmulski" rel="nofollow" target="_blank">https://twitter.com/radekosmulski</a> <a href="https://medium.com/@radekosmulski" rel="nofollow" target="_blank">https://medium.com/@radekosmulski</a> <a href="https://www.kaggle.com/radek1" rel="nofollow" target="_blank">https://www.kaggle.com/radek1</a> <a href="https://www.linkedin.com/in/radek-osmulski-6b935794/?originalSubdomain=pl" rel="nofollow" target="_blank">https://www.linkedin.com/in/radek-osmulski-6b935794/?originalSubdomain=pl</a> Sanyam Bhutani: <a href="https://twitter.com/bhutanisanyam1" rel="nofollow" target="_blank">https://twitter.com/bhutanisanyam1</a> About: <a href="http://chaitimedatascience.com/" rel="nofollow" target="_blank">http://chaitimedatascience.com/</a> A show for Interviews with Practitioners, Kagglers &amp; Researchers and all things Data Science hosted by Sanyam Bhutani. You can expect weekly episodes every Sunday, Thursday available as Video, Podcast, and blogposts. If you'd like to support the podcast: <a href="https://www.patreon.com/chaitimedatascience" rel="nofollow" target="_blank">https://www.patreon.com/chaitimedatascience</a> Intro track: Flow by LiQWYD <a href="https://soundcloud.com/liqwyd" rel="nofollow" target="_blank">https://soundcloud.com/liqwyd</a>

Interview with fast.ai hero: Radek Osmulski | Fast.ai, Learning to Learn | Machine Learning, Kaggle & Blogging