Writing About ML, AI & Programming | Personal Blog — jarmos.netlify.app | Find me on Twitter: @Jarmosan | Newsletter — bit.ly/38QqTQu

Machine Learning

Not sure if a specific business need of your company requires a Data Scientist or an ML Engineer? Then read ahead to find out more about it.

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The Data Scientist VS The ML Engineer: A Showdown | Image designed by Author

Some time ago, a client approached me with a project proposal. He wanted me to use a certain Product-Market framework & write an article from a Data Scientist’s POV. His reasoning, “my Machine Learning skills could prove useful to analyze the drawbacks and/or gaps in the framework to add to it”. And to be clear here, I’m no Data Scientist by craft either.

A couple of emails later, it didn’t take me long to realize his requirements. His target audience for the article were individuals in a non-engineering field. Perhaps, marketing (my assumption) or maybe analysts.

It made me wonder, are my credentials on LinkedIn, GitHub or heck, even Twitter not visible to anyone? The fact that the prospect reached out to me with a data science task instead a software engineering job, points out to something. The issue of ambiguity in the roles of a Data Science/Machine Learning practitioner. …


Software Development

Who needs Linux when you got a fully customized Windows Terminal!

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Heard of the new Windows Terminal (WT), Microsoft has been actively working on recently? You might’ve if you’ve been following my updates on Twitter. I was advocating Microsoft’s effort to make Windows a more developer-friendly platform for quite a while now. And ever since I moved from Ubuntu to Windows for my coding needs, I’ve come to realise how things have changed on Windows-land for the better.

What is This New Windows Terminal?

With that said, WT is a console developed & distributed by Microsoft. It supports a wide variety of shells, the full list of which I’m not aware of. But I’m assured it supports most of the popular ones. Hence, by popularity, Bash/zsh is supported through Windows Subsystem for Linux (WSL) & PowerShell 5.1 …


A sign on the door signifying the store as open to customers.
Photo by Leyre Labarga on Unsplash

Open-Source Software

Your open-source project is no different from a startup. Consider it as one & ensure its success. Here’s a trivial framework to build upon.

The early 2000s witnessed the rise of the software revolution. With it came the idea of “Free & Open-Source Software (FOSS)” after Richard Stallman initiated his Free Software Movement. And in 2020, Open-Source Software is almost the new standard within the software industry. [1] So much so that recruiters often expect new budding software developers to “contribute to” open-source software projects. Or other times, an open-source software (not necessarily free though) is chosen over a proprietary one by the consumers simply due to the quality assurance & trust factor. …


Computer Vision

Deep Learning(DL) techniques are beating the human baseline accuracy rates. Media is going haywire about AI being the next big thing. Everyone is writing a tutorial or two about building a startup or a product using DL. So should you board the hype train too?

A Macbook beside a Typewriter to compare old & new techniques
Photo by Glenn Carstens-Peters on Unsplash

Deep Learning(DL) is undeniably one of the most popular tools used in the field of Computer Vision(CV). It’s popular enough to be deemed as the current de facto standard for training models to be later deployed in CV applications. But is DL the only available option for us to develop CV applications? What about Traditional techniques that have served the CV community for an eternity? Has the time to move ahead & drop working on Traditional CV techniques all together in favor of DL arrived already? …


Opinion

Are you aspiring to be a Data Scientist or a Machine Learning expert? Then allow me to cut through the hype & clear some of the misconceptions you might be already strangled in.

Man facepalming out of disappointment.
Photo by Nik Shuliahin on Unsplash

Around 4 years ago, it was this specific video — MarI/O — Machine Learning for Video Games on YouTube which piqued my interest in Artificial Intelligence & Machine Learning. Being an avid gamer as well as also having an academic background in Economics, I thought to myself, “Oh I already have half of the skills required to make Mario do stuff like this on his own”.

You see, that was the first misconception I had about Machine Learning (or Data Science in general). Little did I know what Reinforcement Learning was, where & how it was used. But did I care? Nope. …


From DCV Team

Submission guidelines for DCV

Guide post showcasing the message from the author about the present article.
Photo by Ivan Aleksic on Unsplash

About the DCV Team.

As already mentioned in a previously published article, A Public Letter From the Team at Discover Computer Vision from the DCV Team, we aspire to create a thriving community of enthusiasts & industry experts comprising both readers & writers alike.

So we request you to read the aforementioned article first before proceeding ahead with the submission guidelines.

1. We Need Original Contributions From You

Before you submit an article to us, we suggest that you ask yourself how original the content of your article is. Is it something that our readers will be hooked on to & appreciate?

If the answer is, YES, go ahead & submit it without a second thought. …


From DCV Team

Who’re we? What do we publish? Why & everything else you might want to know before you publish your article with us.

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Photo by Toa Heftiba on Unsplash

Who Are We?

We’re a bunch of Computer Vision enthusiasts from varying fields of expertise each with our own sets of knowledge & skills to employ CV techniques to our domain.

Over the years as we progressed further in our respective domains, we realized how the field of CV is lacking enough content creators. Although, the field is brimming with researchers & other industry experts, very few of them who were willing to share their knowledge actually found an opportunity to do so.

We also observed that a majority of the blog posts out there are usually riddled with marketing gimmicks & affiliate fluff making it very unattractive to some readers. …


Personal Advice

The wide array of choices for blogging platforms & tools can be overwhelming. As such I was confused too, but you don’t have to be, so read ahead.

Yellow sign post signifying the dilemma of the author about choosing a blogging platform.
Photo by Robert Ruggiero on Unsplash

The day I took a plunge & went full-time freelance, a lingering thought has bothered me ever since; “How do I make my presence known to my prospective clients?”.

A quick Google search on the same question helped me come up with the following quick conclusions:

  1. Share content out there through blog posts.
  2. Be consistent about writing.
  3. Maintain a personal blog site.

Cool! I got the “answers” I was looking for, as I thought & wondered, “how am I supposed to set up a website that I can call my own?

Enter Static Site Generators(SSGs) & SSG Hosts like GitHub Pages & Netlify were the few that I tried, albeit miserably. …


Consider this list opinionated tips before you set foot onto your AI startup. I assure you a thorough read will give you a better perspective to follow.

A basket of crumpled papers signifying wasted & failed ideas.
Photo by Steve Johnson on Unsplash

Most startups fail. In fact, 90% of all startups are bound to fail. They fail to even hold on for the first few years, reports Patel on The Forbes. [1]

And believe it, startups related to Artificial Intelligence are most susceptible to failure. Marketing to “revolutionize” the market adds up even more to that potential threat. Marketing AI startups as revolutionary are so rampant now, the entrepreneurs should feel considerate about their pitch!

As countless AI startups fail, investors grow wary of casting away their capital. Check out what a panel of investors had to say in an interview about investing AI startups — AI Startups Will Fail For The Same Reasons Other Startups…


You mightn’t realize it but if you’ve ample years of experience in a very specific domain of expertise, you might be eligible to be part of a Data Science team.

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Photo by Matthew Feeney on Unsplash

Data Science, dig right into building models, who cares about Domain Knowledge, Right?

Data Science is all in the blaze at the moment! A quick search of the keyword on Google yields not a Wikipedia page of the field but hundreds of tutorials & courses on the first page of the search results.

Although not a bad thing per se, the easily accessible online learning resources helped a lot of self-learners, myself included, to wet our feet into the ocean. Without which, it’s difficult to comprehend trying to learn all by ourselves. …

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