r/learnmachinelearning 22h ago

Career Is it possible to become an AI and ML engineer with a Data Science BS?

2 Upvotes

Hello everyone, I was wondering it is possible to work as an AI engineer and ML engineer with a degree in Data Science. I am currently a sophomore looking into the future of what specializations I could take, and I find that the engineering side of AI and building systems/models is fascinating and intriguing to me. Should I minor in computer science to pick up algorithms and such? Or should I just stick to the path that i'm at now? Eventually, I would like to work remotely.

Thanks a lot!!


r/learnmachinelearning 19h ago

Project Anyone else annoyed when it comes to deploying to the cloud?

0 Upvotes

Hey everyone, hope you're all making good progress on your ML journey! I wanted to share something that came out of a frustration I think a lot of you might relate to. When I was learning machine learning back in university, one of the biggest walls I kept hitting had nothing to do with the actual math or models, it was getting access to real compute. The moment I needed anything heavier than my laptop could handle, I had to connect to the cloud, and that meant writing YAML, picking hardware out of dozens of options, requesting quota increases, waiting on approval, and paying for resources I wasn't even using fully, all before running a single line of real code.

My co-founder felt that exact same frustration, so we built Verlex to abstract the whole cloud deployment pipeline. In two lines of Python, you can deploy anything you want to the cloud, no YAML, no hunting for quota, none of the usual hassle.

What frustrations have you run into when using the cloud? What's the one pain point you wish someone would just solve for you? The more I understand what's actually getting in your way, the better we can shape Verlex to meet your needs. We're currently in beta and it's free to try, so feel free to poke around, and any feedback is welcome!

verlex.dev


r/learnmachinelearning 22h ago

Cybersecurity or ai data

0 Upvotes

I’m really confused guys I don’t know what should I do , I have a bachelor degree in computer science and now I have to decide between data and ai OR claud and internet of objects , knowing that I like alittl of network but I’m scared to not handle it cuz it needs a lot of autofromation ,also the prof himself advised me of ai and data but I’m scared a little of dev cuz I don’t like a lot dev ,what do u think guys !!! Please help


r/learnmachinelearning 20h ago

What language do language models speak?

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2 Upvotes

r/learnmachinelearning 5h ago

Discussion Japan vs Data Centers

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14 Upvotes

r/learnmachinelearning 3h ago

Is it worth learning machine learning without a college degree?

2 Upvotes

Hello friends

I just want to learn machine learning but I have doubts

Because my university degree is not related to this field and is in educational sciences

Now I don't know if I should learn machine learning or not? And can I even make money with it or not?

Thanks for your guidance

#machine_learning


r/learnmachinelearning 2h ago

Project Small update on my no-code game AI tool — and a thank you to the people who tried it

0 Upvotes

Quick post for anyone who likes to follow along. A few days ago I shared DeepEpoch — a no-code desktop app that trains a game-playing AI just by watching you play. You play a 2D game, it records your screen + key presses, and learns to play like you.

First off: thank you to the people who actually downloaded it and gave it a spin. Seeing real users try it means a lot as a solo dev.

Right now I'm focused on making the first-run experience smoother and adding a clearer training status, so you always know what's happening while a model trains.

If you've tried it, I'd love to hear what worked and what didn't. Link in the comments.


r/learnmachinelearning 5h ago

Question How reliable are measures such as accuracy, precision, recall, and f1-score if the assumptions are not met for a logistic regression model?

0 Upvotes

I know the assumptions are crucial for performing statistical inference with logistic regression. But what about for just assessing overall model performance. Can I accurately assess the performance without meeting all the assumptions?


r/learnmachinelearning 7h ago

AI engineer and ML engineer: should I do both?

0 Upvotes

Hi, I just graduated in Bachelor of Computer Science, and I am interested in both AI engineer and ML engineer, and I am also considering what to learn if I do Master in the future.

Currently, my plan is to study both AI engineer (RAG, LLM apis, etc) and machine learning. Besides that, I think want to do projects in both fields in order to find a job.

My concern is should I focus on both or just keep my focus on one field? I am open to learn both at this time, but I also think that focus on one should be better. And for Master, if I do, I should probably go for ML because it seems that AI engineer doesnt need a Master degree. But it also means that I should stick to research my whole life. Is this correct?

I appreciate any advice and guidance, especially if you were in the same place with me or you are in the fields. Thank you so much!


r/learnmachinelearning 8h ago

Tutorial Why I Build The Website Before The Client Pays

0 Upvotes

I’ve been in contact with a lot of web agencies and web developers, and I personally haven’t found many people who run their agency in a more efficient way than I do. A lot of them have too many meetings, wait too long for client approval, don’t know how to price projects, and spend way too much time on each client instead of finishing the work and moving on to the next one.

I’ve been running my agency for four years, and after a lot of trial and error, I’ve managed to make the process as efficient as possible. I wanted to share some of the steps because I think they could be valuable for anyone just starting out.

Running a web agency alone or with a partner isn’t easy because there are a lot of things to take care of. When it comes to client acquisition, I recommend focusing on either cold calling or email automation. Which one you choose depends on whether you run the agency alone or with someone else.

If you have a partner, one person can handle sales while the other focuses on building websites, connecting domains, setting up emails, and taking care of the technical work. If you’re running the agency alone, or neither of you enjoys cold calling, I highly recommend email automation.

That’s what I’ve been doing for years. It’s powerful because you can send emails at scale, set up automatic follow ups, and wait for businesses interested in a new website to reply. While you’re working on one client, another opportunity can come in without you having to stop everything and search manually.

I don’t do regular email automation where I target businesses with no website. I do the opposite and target businesses that already have one.

I use a tool called Swokei to find businesses with websites, add them to campaigns, analyze each site, score it, and generate personalized outreach emails based on problems it finds with the design, layout, speed, SEO, and mobile optimization.I schedule the campaign, set up follow ups, and wait. 

I think this approach is much better for a few reasons. You’re targeting someone who already understands the value of having a website. You’re also not just asking whether they need a redesign. You’re pointing out real problems with their current site, which makes it clear that you actually took the time to look at it. Selling also becomes easier because they’ve already paid for a website before and understand the process.

Inside Swokei, you can choose the goal of the campaign. You can offer a free draft, try to book a meeting, or simply start a conversation. I always choose the free draft because that has worked best for me.

Once you’ve figured out how to get clients, the next part is building the website. I recommend using AI because it makes the process much faster. For anyone who still thinks AI can’t build great websites, I think they’re mistaken. You can use Claude, Base44, Lovable, or any other tool that works for you.

When someone replies interested, I call them and say, “Hey, I saw that you replied to my email. I’ve already built you a free draft of your website. Do you want to take a look?”

Then I invite them to a Google Meet.

At that point, it becomes much harder for them to reject the meeting because they already replied interested and now know you’ve built something for them. During the meeting, I present the website, explain why it’s better than their current one, stack the value, answer their questions, and try to close the deal.

These meetings usually go well because the client isn’t trying to imagine what the website might look like. They can already see a better version of their current site. They also took the time to join the meeting, so taking the next step becomes much easier.

I either take payment during the meeting or send them a contract to sign. Any changes and updates come after that, once we already have a deal in place.

Pricing depends on the business. I charge anywhere from $500 to $3,000 depending on the company, the size of the project, and how much value the website can bring them. I also charge a monthly retainer of around $50 for hosting, maintenance, support, SEO, and future changes.

That’s basically the entire process. Smaller steps, faster delivery, less wasted time, and more money made.


r/learnmachinelearning 8h ago

I’m writing my thesis about AI data labeling and I’m honestly pretty desperate, I need some help

0 Upvotes

Hey everyone
I’m currently writing my university thesis about data labeling for artificial intelligence and honestly I’m starting to feel pretty desperate 😅.
I’ve been searching for information for days through articles, papers, and online discussions, but I keep finding a lot of different opinions and sometimes even contradictory information. It’s becoming really difficult to understand how data labeling actually works in real AI projects.
I would really like to hear from people who work in the field or have experience with machine learning, datasets, or data annotation.
What do you think are the biggest challenges in data labeling today? Cost, time, annotation quality, managing large amounts of data?
And most importantly: how do you usually make sure that annotations are actually correct?
Any personal experience, advice, or insights would honestly help me a lot.
Thanks so much to anyone who takes the time to reply 🙏


r/learnmachinelearning 5h ago

Request How did you start studying Machine Learning?

1 Upvotes

r/learnmachinelearning 10h ago

Help just wanted to know which question bank is being followed by people for MANGOS!!!?? Pls give legitimate resource links

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0 Upvotes

r/learnmachinelearning 18h ago

Anyone else stuck “studying everything” with no real interview plan?

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1 Upvotes

r/learnmachinelearning 17h ago

Stop Pretending MI is Science Right Now

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0 Upvotes

If you repeatedly describe the field as pre-paradigmatic, but seem to treat that as permission to invent local standards of evidence rather than as a demand to make every methodological commitment unusually explicit. The system being unfamiliar does not place it outside philosophy of science, measurement theory, causal inference, or control. It makes those resources more necessary. Building a framework in which compelling candidate explanations can persist without clear identity and defeat conditions is not epistemic humility. It is allowing researcher judgment to substitute for adjudication.


r/learnmachinelearning 22h ago

Discussion After Bun, Cursor tried with a rust rewrite of SQLite

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0 Upvotes

r/learnmachinelearning 14h ago

Looking for an AI Engineering Study Buddy (5–10 hours/week) 🚀

28 Upvotes

Hi everyone! 👋

I'm Milena. I am a software developer with 5 years of experience, and I've recently decided to seriously explore AI Engineering / Machine Learning Engineering.

I've already experimented a bit with stuff like LangChain, RAG, but I'm still figuring out what the roadmap for becoming an AI Engineer actually looks like. There are so many directions -LLMs, RAG, agents, MLOps, fine-tuning, ML, AI infrastructure - that I'd love to explore them with someone instead of learning alone.

I'm looking for a study buddy (or a small group of 2–3 people) who wants to:

  • explore the AI Engineering roadmap together,
  • discuss what technologies and concepts are worth learning,
  • present each other's projects,
  • share interesting resources,
  • exchange ideas on a regular basis.

I can dedicate 5–10 hours per week, and I'm looking for someone with a similar level of commitment.


r/learnmachinelearning 6h ago

3 Months Left Before Placements Hit My Campus — Here's My Full Prep Roadmap . Brutally Honest Feedback Wanted 🙏

0 Upvotes

Hi everyone,

I'm currently in my 7th semester, and mass recruitment drives are expected to hit my campus in the next 3-4 months. I put together a prep roadmap and would really value input from seniors/anyone who's been through this — placed, rejected, whatever, all perspectives welcome.

My current roadmap:

Phase 1 (Days 1-12): Python + SQL

Phase 2: DSA (Python) + Aptitude/Core CS on alternate days

Phase 3 (1 month): ML + Power BI

Phase 4 (1 month): Deep Learning + ML revision + Data Modeling

Phase 5 (15 days): Gen AI

Phase 6 (15 days): Basic MLOps + ML/DL revision

I'm skipping a dedicated project phase since I plan to build projects alongside each topic as I go.

Specifically want feedback on:

  1. Does this order make sense, or should I restructure it?

  2. Am I under-preparing for DSA/aptitude/core CS by only giving them "alternate days," especially if mass recruiters lean heavily on that?

  3. Is it a mistake to skip a dedicated project phase, or is "build as you go" fine?

  4. Anything you'd add/remove/rebalance specifically with placements (not just learning) in mind?

Would really appreciate any real feedback — brutal honesty over politeness, please. Thanks for taking the time to read this 🙏


r/learnmachinelearning 23h ago

Sutskever's List AMA

22 Upvotes

Hi r/learnmachinelearning

I'm Rich Heimann. I'm the author of Sutskever's List.

I'll be here for the next few hours and will answer as many questions as I can.

Looking forward to the discussion!


r/learnmachinelearning 7h ago

Question AI engineer and ML engineer: should I do both?

16 Upvotes

Hi, I just graduated in Bachelor of Computer Science, and I am interested in both AI engineer and ML engineer, and I am also considering what to learn if I do Master in the future.

Currently, my plan is to study both AI engineer (RAG, LLM apis, etc) and machine learning. Besides that, I think want to do projects in both fields in order to find a job.

My concern is should I focus on both or just keep my focus on one field? I am open to learn both at this time, but I also think that focus on one should be better. And for Master, if I do, I should probably go for ML because it seems that AI engineer doesnt need a Master degree. But it also means that I should stick to research my whole life. Is this correct?

I appreciate any advice and guidance, especially if you were in the same place with me or you are in the fields. Thank you so much!


r/learnmachinelearning 29m ago

At what point do you stop learning and just start building?

Upvotes

There's always one more course you could take. One more tutorial to watch. One more concept you probably should understand better.

How do you know when to stop preparing and actually try building something?

Curious whether most people here waited until they felt ready or just picked a project and figured out what they didn't know along the way.


r/learnmachinelearning 4h ago

Project We built a compiler that replaces transformer attention with linear attention — through distillation. No retraining. No new data. One command. Results on GPT-2 (T4, 117 min): • PPL gap: +6.7% • Memory at 8K: 84% less (layer level) •

2 Upvotes

r/learnmachinelearning 4h ago

Need guidance

2 Upvotes

Hey, I'm a computer engineering student trying to figure out what to focus on, and AI is one of the directions I'm considering.

The thing is, I'm not really drawn to the research side — training models, the math behind it. What I want is to build with AI: agents, multi-agent systems, tool use, that kind of thing. More applied than theoretical.

After some research I found Generative AI with Large Language Models on DeepLearning.AI. What do you think — is that the right starting point for what I'm describing, or is it aimed more at the research/fine-tuning side?

And if it's not the right fit, what course or YouTube playlist would you recommend instead?

Thanks in advance 🙏


r/learnmachinelearning 4h ago

Question What video format do autonomous driving companies actually store training data in?

4 Upvotes

when a self-driving company records 1000 hours of driving footage, what format does it end up on disk?Is it all H.265? Or do people actually keep raw frames lying around? And during training do you decode from compressed every epoch or do you pre-decode everything once and eat the storage cost?


r/learnmachinelearning 4h ago

Question 🧠 ELI5 Wednesday

2 Upvotes

Welcome to ELI5 (Explain Like I'm 5) Wednesday! This weekly thread is dedicated to breaking down complex technical concepts into simple, understandable explanations.

You can participate in two ways:

  • Request an explanation: Ask about a technical concept you'd like to understand better
  • Provide an explanation: Share your knowledge by explaining a concept in accessible terms

When explaining concepts, try to use analogies, simple language, and avoid unnecessary jargon. The goal is clarity, not oversimplification.

When asking questions, feel free to specify your current level of understanding to get a more tailored explanation.

What would you like explained today? Post in the comments below!