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Henrik Skogström
  • Turku
  • Finland
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Profile Information

Short Bio:
Valohai is an MLOps platform that enables the whole data science team to work together to launch real-world machine learning solutions. Valohai gives easy access to powerful cloud computing and helps build ML pipelines that train, evaluate and deploy new models.

At Valohai I lead the growth team. My mission is to ensure that no company tries to reinvent the wheel and waste their resources building their own MLOps tooling.
Company:
Valohai
Job Title:
Head of Product
Seniority:
Director
Job Function:
Other
Country
Finland
Number of employees:
1 to 49
Industry:
Technology
LinkedIn Profile:
http://https://www.linkedin.com/in/skogstrom/
Interests:
Contributing, Networking
Topics of Interest
Data Science, Machine Learning, Deep Learning, Data Visualization, Business Analytics, Data Strategy

Henrik Skogström's Blog

When Should a Machine Learning Model Be Retrained?

Posted on November 30, 2020 at 11:11pm 0 Comments

A few years ago, it was extremely uncommon to retrain a machine learning model with new observations systematically. This was mostly because the model retraining tasks were laborious and cumbersome, but machine learning has come a long way in a short time. Things have changed with the adoption of more sophisticated MLOps solutions.

Now, the…

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When Is a Machine Learning Model Good Enough for Production, and How to Stress About It Only Once?

Posted on November 18, 2020 at 5:30am 0 Comments

As you start incorporating machine learning models into your end-user applications, the question comes up: “When is the model good enough to deploy?”

There simply is no single right answer.

There is no clear-cut measure of when a machine learning model is ready to…

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The MLOps Stack

Posted on October 26, 2020 at 12:57am 0 Comments

What is MLOps (briefly)

MLOps is a set of best practices that revolve around making machine learning in production more seamless. The purpose is to bridge the gap between experimentation and production with key principles to make machine learning reproducible, collaborative, and continuous.

MLOps is not dependent on a single technology or platform. However, technologies play a significant role in practical…

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