Shownotes Transcript
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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