Andrew Ng's Stanford Machine Learning lecture series, posted on YouTube as a playlist. It covers core machine learning topics with the underlying math and motivations, presented as proper lectures.

Commenters recommend it as an accessible way to get the main ideas of machine learning, and one notes it includes the underlying math and motivations rather than flashy visuals.

On Reddit (4)

1. Recommendsngc4321r/learnmachinelearning2023in “What is a good text-based course for learning ML?”

   I know you said videos won't do it, but here's a lecture by Andrew Ng which I used. It's not like other videos with fancy graphics, sounds, etc where much is much left to be desired . It's a proper lecture (albeit shorter), some of which he uses for his Stanford lectures, including the underlying…

2. Recommends_RalphBayer_r/learnmachinelearning2020in “What would be the most obvious way I could implement ML in my work?”▲ 1

   I'm sure there will be some tutorials for this on YouTube. You could also take a machine learning course (not related to your machine learning problem) to get the main idea behind what machine learning actually is, I recommend…

3. MentionsGlobbir/Python2022in “Write real AI code”

   You definitely can omit using Pandas, but it's just for processing data in tables. Will you also not use existing libraries that read json or csv when you load your data and parse it yourself? How about opening images, you can use existing library and do imopen(), or you will have to decode jpeg…

4. Mentionsl_am_wildthingr/learnprogramming2021in “Pose Estimation AI with Tensorflow Help (Urgent)”▲ 2

   If you havent learned ML in depth then this is not something you just want to start and see where it goes. It seems like you havent even learned an ML library yet. If you really want to learn ML, brush up on stats, calculus, and linear algebra then take andrew ng's udemy course then stanford's…

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