Why and How to Monitor Machine Learning Models
This is the 41st edition of CrunchX and here are the stories and resources we thought were worth spending time on.
One of the most important tools in any software engineer’s toolbox is a good terminal and the ability to see a lot of information, presented clearly, on the screen. While my favorite (bring a macOS user) is iTerm2 with its tabs, I know a lot of people who use tiled window managers inside terminals themselves. Terminator is a great example of this “genre” and if you’ve never heard of them before or aren’t sure how they work, it’s worth checking out. Written by Anuj Sharma on It’s Foss and editorially selected by Dr Stuart Woolley. Read the article here:
I’ve never programmed too much in Forth myself (but I tried the language once in the 1980s, then a few years ago), but I still know people who write niche commercial software in it – mainly in embedded systems. Ray Duncan’s article “A Forth Apologia” is a snapshot in time, originally published in 1988, and offers a unique view into the history and philosophy of the language. If you’re a computer scientist and are interested in “could have been” languages or even want to try it, this is a great read. Written by Ray Duncan on Holonforth and editorially selected by Dr Stuart Woolley. Read the article here:
Companies hire Data Scientists to develop ML models and conduct AI experiments. This article introduces 5 features that can be useful when upgrading data science productivity within an organization. Written by Isaac Sacolick on InfoWorld and editorial selection by Christianlauer. Read the article here:
It is not only important to develop machine learning models, it is also necessary to learn how to monitor them and keep them reliable for further analysis. This article specifically describes why it is important and how to monitor machine learning models. Written by Isaac Sacolick on InfoWorld and editorial selection by Christianlauer. Read the article here:
Data can be found everywhere these days. Images can therefore also be good sources. This article introduces eight tools that help extract and manipulate data from images and images. Written by Vijay Singh Khatri on KDNuggets and editorial selection by Christianlauer. Read the article here:
This can be good for your wallet when working with data that helps solve real-world problems. This article describes three projects that do just that. Written by Nate Rosidi on KDNuggets and editorially selected by Christianlauer. Read the article here:
How many times have you missed the quote? Most of the time, these are just educated guesses. Read this story for the laws of estimation. These should help ease the pain of estimates. Written by Maarten Dalmijn on Maarten’s Newsletter and editorial selection by Miloš Živković. Read the article here:
All architecture has a cost. And what I love about this story is the profiling code. Premature optimization is the root of all evil. So use a profiler beforehand. Written and published by Kirill Rogovoy and editorial selection by Miloš Živković. Read the article here:
I’m still looking for a reason to avoid touching any Python code – to me it’s just a language not well enough suited to be used. It’s interpreted, has no meaningful multi-threading capability, chokes on huge datasets, and who does the fixed formatting in 2022 anyway?
To that end, I’d always go back to my old trusty (and favorite) C for low-level programming that requires speed, use Go simply for higher-level ease-of-use and speed, and lately Julia because c It’s a bit of both… Jakob Nybo Nissen has two great blog posts about Julia, “What’s Wrong With Julia” and “What’s Great With Julia” that really tell you everything what you need to know about why you should try diving into the language if you haven’t already. Plus, it’s fun — and that can’t be said of many modern languages! Written by Jakob Nybo Nissen on Viralinstruction and editorial selection by Dr Stuart Woolley. Read the article here:
What’s wrong with Julia: https://viralinstruction.com/posts/badjulia/
What’s Great About Julia: https://viralinstruction.com/posts/goodjulia/
#Importance #Monitoring #Machine #Learning #Models