Machine Learning Engineered
Charlie You
This podcast helps Machine Learning Engineers become the best at what they do. Join host Charlie You every week as he talks to the brightest minds in data science, artificial intelligence, and software engineering to discover how they bring cutting edge research out of the lab and into products that people love. You'll learn the skills, tools, and best practices you can use to build better ML systems and accelerate your career in this flourishing new field.
Categories: Technology
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Previous episodes
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32 - Diving Deep into Synthetic Data with Alex Watson of Gretel.aiTue, 20 Apr 2021
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31 - A Practical Approach to Learning Machine Learning with Radek Osmulski (Earth Species Project)Tue, 30 Mar 2021
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30 - From Data Science Leader to ML Researcher with Rodrigo Rivera (Skoltech ADASE, Samsung NEXT)Tue, 23 Mar 2021
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29 - The Future of ML and AI Infrastructure and Ethics with Dan Jeffries (Pachyderm, AI Infrastructure Alliance)Tue, 16 Mar 2021
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28 - Developing Feast, the Leading Open Source Feature Store, with Willem Pienaar (Gojek, Tecton)Tue, 09 Mar 2021
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27 - Bringing DevOps Best Practices into Machine Learning with Benedikt Koller from ZenMLTue, 02 Mar 2021
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26 - Starting an Independent AI Research Lab with Josh Albrecht from Generally IntelligentTue, 23 Feb 2021
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25 - Industrial Machine Learning and Building Tools for Data and Model Monitoring with Evidently AI Co-Founders Elena Samuylova and Emeli DralTue, 16 Feb 2021
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24 - Managing Data Science Teams and Hiring Machine Learning Engineers with Harikrishna Narayanan (YC Stealth Startup)Tue, 09 Feb 2021
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23 - Lessons Learned From Hosting the ML Engineered Podcast (Charlie Interviewed on the ML Ops Community podcast)Tue, 02 Feb 2021
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22 - Building a Post-Scarcity Future using Machine Learning with Pavle Jeremic (Aether Bio)Tue, 19 Jan 2021
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21 - Best of ML Engineered in 2020 Part 1 - ML EngineeringTue, 05 Jan 2021
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20 - Solocast - Holiday GratitudeTue, 22 Dec 2020 - 0h
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19 - Music Information Retrieval at Spotify and the Future of ML Tooling with Andreas Jansson of ReplicateTue, 15 Dec 2020
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18 - Luigi Patruno: ML in Production, Adding Business Value with Data Science, "Code 2.0"Tue, 08 Dec 2020
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17 - Coding Career Tactics - Salary Negotiation, Public Speaking, and Creating Your Own Luck w/ Shawn "swyx" Wang (AWS)Tue, 01 Dec 2020
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16 - Yannic Kilcher: Explaining Papers on Youtube, Why Peer Review is Broken, and the Future of the FieldTue, 24 Nov 2020
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15 - How to Get Ahead in Machine Learning with Zak Slayback (1517 Fund)Tue, 17 Nov 2020
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14 - Why Multi-Modality is the Future of Machine Learning w/ Letitia Parcalabescu (University of Heidelberg, AI Coffee Break)Tue, 10 Nov 2020
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13 - Moin Nadeem (MIT): The extraordinary future of natural language modelsTue, 03 Nov 2020
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12 - Peiyuan Liao: The 20 Year-Old Kaggle GrandmasterTue, 27 Oct 2020
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11 - Shreya Shankar: Lessons learned after a year of putting ML into productionTue, 20 Oct 2020
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10 - Josh Tobin: Research at OpenAI, Full Stack Deep Learning, ML in ProductionTue, 13 Oct 2020
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9 - Sanyam Bhutani: Chai Time Data ScienceTue, 06 Oct 2020
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8 - Devon Bernard: "If you can sell it, I can build it"Tue, 29 Sep 2020
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7 - Catherine Yeo: Fairness in AI and AlgorithmsTue, 22 Sep 2020
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6 - Charles Yang: Machine Learning for Scientific ResearchTue, 15 Sep 2020
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5 - swyx (Shawn Wang): Coding Career StrategyTue, 08 Sep 2020 - 0h
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4 - Solocast: Learning Machine LearningTue, 01 Sep 2020 - 0h
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3 - Karthik Suresh: Advice for Computer Science StudentsTue, 01 Sep 2020
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2 - Jordan Dunne: What Engineers Should Know about Product and Program ManagementTue, 01 Sep 2020
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1 - Introducing Machine Learning EngineeredTue, 18 Aug 2020 - 0h
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