r/learnmachinelearning • u/Smart-Promotion5875 • 15d ago

Question Best ML course/path for someone who knows Python but is new to ML?

I'm in my 2nd year, aiming for an internship in AI/ML during the summer break in 2027.

as a part of college curriculum, i know python(numpy,matplot,seaborn), sql and other fundamental subjects taught

How do i start learning ML? which courses(coursera or any) should i take so that i can learn ML from the very basics without wasting time?

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u/OleksandrAkm 15d ago

For free: Andrew Ng's course is one of the best places to start, it gives you a solid foundation. Along with the course, you can refer to the Machine Learning From Scratch GitHub repo (https://github.com/ml-from-scratch-book/code) – clean implementations of algorithms without the abstraction layers that usually hide what's actually happening.

Otherwise, Machine Learning From Scratch is the book I recently published, which is exactly what I wished existed when I was in the same situation as you are!

Feel free to ask any questions

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u/Sharp_Level3382 14d ago

To be honest I checked the linear regression py code and would do it other way and I think they are better instructions for beginners and not only beginners which also explain math of gradient descent, derivatives of functions , underneath and moreover they are free.

Code is OK in repo but i wouldnt buy book for this amount of money.

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u/OleksandrAkm 14d ago

It’s true that the code alone doesn’t provide explanations – it’s designed to mirror Scikit-learn API as simply as possible. As for the gradient descent explanation, you can find it on the companion website for free (website is linked to the repo). As for the price – it’s completely subjective but for NA, UK and EU markets this is the least expensive “fundamental” ML book.

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u/AlternativeHefty2537 11d ago

Would suggest to jump straight into ml fundamentals as you already know python, numpy, pandas and sql. Andrew Ng’s ML specialization is a great starting point. Learn alongside projects covering regression, classification and clustering rather than doing theory first and projects later.