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Everyone, and welcome back to this class.

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In this section, I'm going to go over some common questions that students have and some general tips

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that have helped students in the past.

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Please keep in mind that this is not a core part of the course.

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These are just common general questions that students have had about machine learning or about my courses

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in general.

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I realize that it's not useful for everyone, but please keep in mind that it's useful for someone.

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There are a few people out there that tell me they think all the lectures should only answer their questions,

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but not anyone else's questions.

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So just keep in mind that many of your fellow students have asked me these questions in the past.

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And in order to answer those questions in a scalable way, I've created the section.

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Please try not to hold it against me, as this may not directly help you, but it may help your fellow

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students.

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Please also keep in mind that the appendix section in no way takes away from the core content, all

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the material provided for the topic matter is exactly what I wanted to provide.

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These appendix lectures are simply extra stuff.

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So these appendix lectures do not displace any technical content.

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If the appendix section did not exist, the technical part of this course would be exactly the same

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as it is now.

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So just remember this.

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The appendix is in addition to the technical content.

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It does not displace any technical content.

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You get all the technical content that I intended.

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Also, keep in mind that you're always able to select the lecture you want using the user interface,

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that's this thing.

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If you don't know how to use the video player to select a lecture, please ask me how on the Q&amp;A or

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contact your support so you're encouraged to select the lectures you want to watch manually and skip

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lectures you don't want to watch.

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Also, keep in mind, however, that a common mistake is in thinking that this material is not going

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to help you when in reality it will.

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For example, I come across students all the time who have no idea how to get started implementing machine

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learning algorithms and code or why we are doing so in the first place.

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Then I come to find that they have never watched how to code by yourself.

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So I think it goes without saying that if you don't know how to code by yourself, you should probably

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watch the lecture, how to code by yourself.

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Same thing goes for the other lectures in this section.

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All right, let's get to the lectures.
