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I was tasked to help in the practical sessions of the Machine Learning course in my university, the plan was to give exactly the same materials as this course. We should be teaching the assignments of this course as lab sessions.

The main problem is that this course is being given as the main source for teaching ML in the university(lectures and lab session), I don't have any previous teaching experience but I personally think that it is better to teach using some famous textbook like Ethem Alpaydin's Intro to ML book.

I'm looking mainly for the pros and cons of both approaches if you have any experience with any(or both) of them.

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    $\begingroup$ Hmmm. Do you have a copyright problem? In much of the world you would. $\endgroup$
    – Buffy
    Mar 1, 2022 at 20:46
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    $\begingroup$ Umm was that book really published in 2004!? I feel like anything pre-resnet (2015) would be pretty useless for students that intend to contribute to the field or work in industry. Maybe a statistics book would be better before jumping into modern ml. $\endgroup$
    – Navin
    Mar 23, 2022 at 11:13
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    $\begingroup$ The third edition of the book was published in 2014, so yeah it is kinda of old. Thanks for the suggestion. $\endgroup$
    – subspring
    Mar 23, 2022 at 11:31
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    $\begingroup$ Yeah 2014 is pretty old. I might be biased since my research is focused on something that only became practical in the last decade (GANs) but if I were you, I’d do a quick refresher on ml/statistics (logistic regression, ridge regression, bias/variance tradeoff), and then skip ahead to deep learning. The linked course looks decent to me. You could probably skip/skim over SVMs, but besides that it looks like a reasonable intro to ML. $\endgroup$
    – Navin
    Mar 23, 2022 at 12:12
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    $\begingroup$ Thanks a lot, your suggestions are really helpful. $\endgroup$
    – subspring
    Mar 23, 2022 at 13:58

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