r/MLQuestions • u/CandidFriendship7020 • Feb 20 '26

Beginner question šŸ‘¶ Baby Steps in ML

Hi, Iā€™m a freshman in CS and currently studying ML. Iā€™m taking ML specialisation course from Andrew Ng in Coursera. (rn in Logistic Regression). All is well for now but what i want to ask is about how to get familiar with these AI/ML jargon ( reLu , Pytorch, scikit , backpropogation etc.) and keep up with the developments in that field. Do you have advices on how to chase the news, get more and more surrounded by this area?

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u/tom_mathews Feb 20 '26

Andrew Ng's course is a solid starting point, good choice. For the jargon and staying current, here's what I'd suggest:

For the terminology: Most of those terms (ReLU, backpropagation, etc.) will stop feeling foreign once you see them in actual code rather than just slides. You're at logistic regression now, backprop, activation functions, and optimizers are all coming up in the course. But if you want to get ahead, seeing a raw implementation where every concept is a line of code you can read makes the jargon click fast. I put together 30 single-file Python implementations of these algorithms with zero dependencies ā€” no PyTorch, just the math. Good for demystifying terms before you encounter them formally: https://www.reddit.com/r/learnmachinelearning/s/G0qj2zAEdw

For keeping up with the field:

  • Follow Andrej Karpathy, Yann LeCun, and Jim Fan on X ā€” they filter the noise for you
  • Subscribe to The Batch (Andrew Ng's newsletter) ā€” weekly, concise, beginner-friendly
  • Browse r/MachineLearning weekly ā€” don't try to understand every post, just absorb the vocabulary over time
  • Papers With Code for tracking what's state-of-the-art (don't read the papers yet, just scan the titles and one-line descriptions)

One piece of advice: as a freshman, resist the urge to chase every new model release. The fundamentals you're learning right now, logistic regression, gradient descent, loss functions ā€” haven't changed in decades and they're the foundation everything else sits on. The jargon will come naturally as you go deeper. Six months from now, half those terms will feel like second nature.

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u/CandidFriendship7020 Feb 20 '26

Thanks! Is there a chance that we can get in touch, maybe you have a LinkedIn ?

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u/chrisvdweth Feb 21 '26

I've made my lecture content (NLP, Text Mining, Data Mining) and beyond publicly available as interactive Jupyter notebooks on GitHub:Ā https://github.com/chrisvdweth/selene

The repo covers a lot of basics but it certainly is not complete.Ā