🖥️ A plain and simple take on ML.NET vs Python

So, I’ve been working with data for a while now, and something’s always bugged me — Python is hard. Everyone keeps saying it’s the best for data science, but honestly, I don’t get it. I’ve used it before, and sure, it works… but it’s messy.

Let me explain.

🧩 What’s Wrong with Python?

First of all, Python has way too many packages. You’ve got pandas, numpy, matplotlib, scikit-learn, and so on. You need to install them all, learn how each one works, and most of the time they all do things in different ways.

Even simple things, like loading a CSV or splitting up data, can take more steps than it should. I often find myself googling the smallest things, just trying to remember some odd line of code.

And when you want to share your Python project or move it somewhere else? That’s when “package hell” starts. Something’s always the wrong version, or something’s missing, or it just refuses to work on another machine.

🔍 I Did Some Research…

Since I’m a C# developer, I decided to look around and see if there’s something out there that fits better with what I already know. That’s when I found out about ML.NET, and honestly, I was surprised how far Microsoft has come with it.

You can do proper machine learning: train models, clean data, make predictions — all straight from C#. And it’s fast, neat, and fits right into the kind of projects I already work on.

✅ Why C# Makes Sense (for Me)

C# just makes more sense to me. The code is easier to follow, the error messages are clearer, and I don’t need a dozen add-ons just to get going. It runs well, and I can build full apps around it without switching tools or languages.

Also, I don’t have to mess with virtual environments, Jupyter notebooks, or Anaconda. It’s all there in one place.

But just to be clear — I’m not saying I only use C#. I know Python is still a big deal in data science. I just don’t think everyone needs to jump on Python if they already know another solid language. Especially if the tools for that language are catching up fast — and ML.NET really is.

💡 Why Python’s Still on Top

Python is still the go-to for most people in data science. And I get it — it was first to the party. Most tutorials, courses, and examples are in Python. So if you’re starting from scratch, that’s probably where you’ll end up.

But here’s the thing: I think a lot of people use Python just because they don’t know there are other options. It’s not always the best tool — it’s just the most familiar one.

🔚 Final Thoughts

I’m not against Python. I’ve used it, and I’ll probably use it again when I have to. But if I have a choice, I’d rather use C# and ML.NET. It’s clean, simple, fast, and it does the job.

So if you’re like me and come from a C# background, don’t feel like you have to learn Python just to do machine learning. It’s not your only option anymore — and that’s a good thing.