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I just graduated from my university with a Computer Science Bachelor.

Because of this, I have good Python knowledge, coded a reinforcement learning AI, did machine learning ABCs with Iris flower detection and figuring out digits from the MNIST dataset using ANNs and CNNs, but that's the extent of my knowledge with respect to machine learning. I also have a decent background with linear algebra.

Given my position, what would you say is the best way for me to study Machine Learning? Self study? If so, could you recommend some resources?

Thanks!!

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  • $\begingroup$ I think the answer depends a bit on what kind of learner you are. So are you a better book learner or videos. Do you approach things from the mathematical side first, or do you like to try code and then understand the math after seeing the method in practice? There is just a lot to learn in terms of ML. It is totally doable, but just need to know where you are coming from. $\endgroup$ – krishnab Aug 27 '19 at 19:41
  • $\begingroup$ Cant comment on sadly (less then 50 points). So here's to hoping you will come across this @krishnab. I do prefer learning visually, so videos would be ideal. Re your second question, I would rather learn implementations of machine learning algorithms and work backwards to understand the mathematics behind the model. $\endgroup$ – user257453 Aug 27 '19 at 20:24
  • $\begingroup$ @user257453, I encourage you to merge your accounts (see cs.stackexchange.com/help/merging-accounts); this will let you leave comments and edit your question to clarify it. That said, opinion-oriented questions often aren't a good fit here, so the question might or might not fare well. $\endgroup$ – D.W. Aug 28 '19 at 3:51

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