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Product Management in Machine Learning, MLOps Engineering Labs Recap

Posted Mar 03, 2021 | Views 344
# Interview
# Cultural Side
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SPEAKER
Laszlo Sragner
Laszlo Sragner
Laszlo Sragner
Founder @ Hypergolic

Laszlo worked as a quant researcher at multiple investment managers and as a DS at the world's largest mobile gaming company. As Head of Data Science at Arkera, he drove the company's data strategy delivering solutions to Tier 1 investment banks and hedge funds. He currently runs Hypergolic (hypergolic.co.uk) an ML Consulting company helping startups and enterprises bring the maximum out of their data and ML operations.

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Laszlo worked as a quant researcher at multiple investment managers and as a DS at the world's largest mobile gaming company. As Head of Data Science at Arkera, he drove the company's data strategy delivering solutions to Tier 1 investment banks and hedge funds. He currently runs Hypergolic (hypergolic.co.uk) an ML Consulting company helping startups and enterprises bring the maximum out of their data and ML operations.

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SUMMARY

How my experience in quant finance and software engineering influenced how we ran ML at a London Fintech Startup. How to solve business problems with incremental ML? What's the difference between academic and industrial ML?, This is a deep dive into the most recent MLOps Engineering Labs from the point of view of Team 3. Artem, Dimi, Laszlo, and Paulo chose to use Yelp Review dataset for training an NLP model for classifying provided texts as positive or negative reviews. The data includes reviews on restaurants, museums, hospitals, etc., and the number of stars associated with this review (0–5). Team 3 modeled this task as a binary classification problem: determining whether the review is positive (has >=3 stars) or negative (otherwise). Check the diagram Link here.

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Posted Feb 23, 2021 | Views 246
# Open Source
# Panel
# Model Serving
# Interview