Machine Learning for Developers

By Satish Chandra Gupta

ML4Devs is a biweekly newsletter for software developers. The aim is to curate resources for practitioners to design, develop, deploy, and maintain ML applications at scale to drive measurable positive business impact. Each issue discusses a topic from a developer’s viewpoint.

ML4Devs is a biweekly newsletter for software developers.

The aim is to curate resources for practitioners to design, develop, deploy, and maintain ML applications at scale to drive measurable positive business impact.

Each issue discusses a topic from a developer’s viewpoint.

By subscribing, you agree with Revue’s Terms of Service and Privacy Policy and understand that Machine Learning for Developers will receive your email address.

1.33K

subscribers

7

issues

#7・

MLOps -- the dust has not settled yet (ML4Devs Newsletter, Issue 7)

You must have noticed the buzz about MLOps. MLOps is the lifecycle, process, and tools for deploying machine learning models in production.There has been an explosion of MLOps vendors and tools. Many of those are named as xyzFlow or xyzML:KubeFlowMLFlowMetaFl…

 
#6・

Data Visualization (ML4Devs Newsletter, Issue 6)

When you see informative charts and infographics, what is your first reaction? I wonder how you decide which chart type to use.In this issue, I will share some of the best resources I found.

 
#5・

Setting up Data Collection (ML4Devs Newsletter, Issue 5)

Cliché: Without data, there can be no data science.But it is true.While learning data science, we mostly use public data sets or scrape data off the web. But in ML-assisted products, most of the data is generated and collected through business applications.Th…

 
#4・

Best Path for Developers to Get into Machine Learning (ML4Devs Newsletter, Issue 4)

The most frequent question I get from developers is: what is the best way to get into Machine Learning?A few years back, my response was:Google for best resources and learnFind problems at work and apply what you learnRepeatThough that response was honest and…

 
#3・

To be agile, or not to be (ML4Devs Newsletter, Issue 3)

I guess the answer depends on whom do you ask.I have seen many Data Scientists bitterly oppose Agile and Scrum:6 Reasons why I think Agile Data Science does not workWhy Scrum is awful for data scienceWhy data science doesn't respond well to Agile methodologie…

 
#2・

ML Model Testing (ML4Devs Newsletter, Issue 2)

If your machine learning model has a high correctness score on the holdout test data set, is it safe to deploy it in production?

 
#1・

Machine Learning for Developers (ML4Devs Newsletter, Issue 1)

Wish you all a very happy new year! I hope that this year we finally put the COVID pandemic behind us.Last year, I started ML4Devs as a weekly newsletter but could not sustain the pace. So this year, I am restarting it as a biweekly to make it more sustainabl…