We explore topics of data science, machine learning and MLOps. Subscribe below to receive the best bits monthly.
Makefile: the secret weapon for ML project managementJuha 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.
Top-3 industries that need artificial intelligence solutions the most in 2022Viktoriya Kuzina
We look at industries with the highest need for artificial intelligence solutions in 2022, why they need it, and gives example use-cases.
IDEs for Data Science: What every data scientist should know about programming toolsJuha 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.
Valohai Mentioned in 2022 Gartner® Market Guide for DSML Engineering Platforms ReportViktoriya Kuzina
Valohai has been mentioned as a Representative Vendor by Gartner® in the “Market Guide for DSML Engineering Platforms”
What every data scientist should know about the command lineJuha 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!
Three ways to mitigate model output riskEikku 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.
Mike Del Balso joins Valohai’s advisory boardEero 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.
Experimentation at Scale: a Q&A with Serg Masís from SyngentaJuha 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.
One size doesn't fit all - How the use case affects ML system complexityEikku 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.
Docker for Data Science: What every data scientist should know about DockerJuha 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.