Getting Machine Learning Models Into Production?

Machine Learning Engineer is one of the fastest growing professions on the planet.  Liran Hason, co-founder and CEO of Aporia, joins us to discuss this new field and how folks can learn the skills and gain the experience needed to become an ML Engineer!

00:00:59 Introductions

00:01:44 How Liran got started making websites

00:07:03 College advice for getting involved in real-world experience

00:12:51 Jumping into the unknown

00:15:22 ML engineering

00:20:50 The missing part in data science development

00:29:16 How to build skills in the ML space

00:37:01 A horror story

00:41:34 Model loading questions

00:47:36 Must-have skills in an ML resume

00:50:41 Deciding about data science

00:59:08 Rust

01:06:27 How Aporia contributes to the data science space

01:14:26 Working at Aporia

01:16:53 Farewells

Resources mentioned in this episode:

Links:

• Liran Hason:
  • Linkedin: https://www.linkedin.com/in/hasuni/
• Aporia:
  • Website: https://www.aporia.com/
  • Twitter: https://twitter.com/aporiaai
  • Linkedin: https://www.linkedin.com/company/aporiaai/
  • Github: https://github.com/aporia-ai
• The Mom Test (Amazon):
  • Paperback: https://www.amazon.com/Mom-Test-customers-business-everyone/dp/1492180742
  • Audiobook: https://www.amazon.com/The-Mom-Test-Rob-Fitzpatrick-audiobook/dp/B07RJZKZ7F

References:

• 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_deployment
• Coursera ML Specialization (Stanford): https://www.coursera.org/specializations/machine-learning-introduction
• Auto-retraining: https://neptune.ai/blog/retraining-model-during-deployment-continuous-training-continuous-testing

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