Valohai Blog

We explore topics of data science, machine learning and MLOps. Subscribe below to receive the best bits monthly.

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July 25, 2022

Makefile: the secret weapon for ML project management

Juha KiiliJuha Kiili

What if I told you there is a simple, free, lightweight tool for weaponizing any CLI-based ML project. All the commands are nicely wrapped and accessible via shortcut aliases and only a TAB keypress away. This tool is easily installable and super robust for all operating systems! It is called Make.

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July 18, 2022

Top-3 industries that need artificial intelligence solutions the most in 2022

Viktoriya KuzinaViktoriya Kuzina

We look at industries with the highest need for artificial intelligence solutions in 2022, why they need it, and gives example use-cases.

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July 04, 2022

Five things to know about Jupyter notebooks

Juha KiiliJuha Kiili

Here are some tips and tricks for Jupyter notebook with step-by-step guides: from running shell commands to changing the notebook theme - easily!

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June 20, 2022

IDEs for Data Science: What every data scientist should know about programming tools

Juha KiiliJuha Kiili

There is absolutely nothing wrong with notebooks, and they are fantastic for many use-cases, but they are not the only option for writing programs. Too many get stuck in the vanilla notebook and do not realize what they are missing out on.

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June 09, 2022

Valohai Mentioned in 2022 Gartner® Market Guide for DSML Engineering Platforms Report

Viktoriya KuzinaViktoriya Kuzina

Valohai has been mentioned as a Representative Vendor by Gartner® in the “Market Guide for DSML Engineering Platforms”

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June 06, 2022

Distributed learning to boost your AI efforts

Ruksi KorpisaraRuksi Korpisara

We want to talk about what distributed learning is in brief and focus more on why having this feature is a valuable tool for your business.

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May 23, 2022

Tracking the carbon footprint of model training

Magdalena SteniusMagdalena Stenius

What started as a fun side project for our developer Magda turned out to be a proud addition to the platform. Valohai can now estimate the carbon emissions of cloud instances. Yay!

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May 16, 2022

What every data scientist should know about the command line

Juha KiiliJuha Kiili

Almost any programming language in the world is more powerful than the command line. Why would you even bother doing anything on it? Don't be fooled: the modern command line is rocking like never before!

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May 09, 2022

Is online inference causing your gray hair?

Viktoriya KuzinaViktoriya Kuzina

Suppose you find your projects to be in the gray area between the extremes of delayed and real-time inference where you can go with either one, ask yourself if you can delay. And if you can, you should!

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April 26, 2022

MLOps for IoT and Edge

Henrik SkogströmHenrik Skogström

There's a new wave of automation being enabled by the combination of machine learning and smart devices. With the complexity of use cases and amount of devices increasing, we'll have to adopt MLOps practices designed for IoT and edge.

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March 30, 2022

Three ways to mitigate model output risk

Eikku KoponenEikku Koponen

Machine learning comes with new types of risk. We need to minimize the risk by addressing how we develop these algorithms and also how we apply these algorithms in the real world. In this article, we'll look at three ways of mitigating the latter – i.e. output risk.

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March 15, 2022

Mike Del Balso joins Valohai’s advisory board

Eero LaaksonenEero Laaksonen

Mike Del Balso is a familiar name to most in the machine learning community. He's one of the pioneers in the MLOps space and has laid the foundations for operational machine learning at Uber, Google, and most recently, Tecton.

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March 10, 2022

Experimentation at Scale: a Q&A with Serg Masís from Syngenta

Juha KiiliJuha Kiili

Syngenta is a leading provider of agricultural science and technology focused on seed and crop protection products aiming to improve global food security by enabling millions of farmers to make better use of available resources.

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February 24, 2022

One size doesn't fit all - How the use case affects ML system complexity

Eikku KoponenEikku Koponen

Algorithms have become faster, fancier, and more complex in the past couple of years. Still, they haven't gained as much complexity as the systems around algorithms. In this article, we'll discuss three examples of systems complexity.

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February 14, 2022

Docker for Data Science: What every data scientist should know about Docker

Juha KiiliJuha Kiili

Docker isolates the software from all other things on the same system. A program running inside a "spacesuit" generally has no idea it is wearing one and is unaffected by anything happening outside.

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