Introductions00:01:44 How Liran got started making websites00:07:03 College advice for getting involved in real-world experience00:12:51 Jumping into the unknown00:15:22 ML engineering00:20:50 The missing part in data science development00:29:16 How to build skills in the ML space00:37:01 A horror story00:41:34 Model loading questions00:47:36 Must-have skills in an ML resume00:50:41 Deciding about data science00:59:08 Rust01:06:27 How Aporia contributes to the data science space01:14:26 Working at Aporia01:16:53 FarewellsResources mentioned in this episode:Links:Liran Hason:Linkedin: https://www.linkedin.com/in/hasuni/Aporia:Website: https://www.aporia.com/Twitter: https://twitter.com/aporiaaiLinkedin: https://www.linkedin.com/company/aporiaai/Github: https://github.com/aporia-aiThe Mom Test (Amazon):Paperback: https://www.amazon.com/Mom-Test-customers-business-everyone/dp/1492180742Audiobook: https://www.amazon.com/The-Mom-Test-Rob-Fitzpatrick-audiobook/dp/B07RJZKZ7FReferences:Shadow Mode: https://christophergs.com/machine%20learning/2019/03/30/deploying-machine-learning-applications-in-shadow-mode/Blue-green deployment: https://en.wikipedia.org/wiki/Blue-green_deploymentCoursera ML Specialization (Stanford): https://www.coursera.org/specializations/machine-learning-introductionAuto-retraining: https://neptune.ai/blog/retraining-model-during-deployment-continuous-training-continuous-testingIf you’ve enjoyed this episode, you can listen to more on Programming Throwdown’s website: https://www.programmingthrowdown.com/Reach out to us via email: [email protected] can also follow Programming Throwdown on Facebook | Apple Podcasts | Spotify | Player.FM Join the discussion on our DiscordHelp support Programming Throwdown through our Patreon

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