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ragdoll438 t1_j2bursi wrote

Why do you think your thesis has to involve deep learning? you should first focus on problem and not technic. DL is useful when you have millions of data points and in most of the use cases classical ML/statistical learning is enough

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Ashraf_mahdy OP t1_j2cxhvw wrote

I use the term DL/ML/AI interchangeably so maybe I am mistaken in this regard.
However, I did research the difference between Statistical learning and ML and the idea is that statistical learning is about relations between variables whereas DL/ML is about learning from a "random" so to speak dataset. In my case one time events can affect the statistical learning outcomes, however I am planning a "fall-back" method of statistical learning as well if that makes sense

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psychorameses t1_j2e63yf wrote

That distinction isn't real. In that regard, both techniques learn exactly the same thing: a best fit curve. The difference is how complicated that curve needs to be. Unless you are trying to do something specific like computer vision or natural language processing, you really don’t need DL. If you are working with simple tabular data, basic ML like linear regression will be more than enough.

In any case, the feedback for most ML projects is to start with a simple regression technique and only start complicating your models if you aren’t getting what you want. You’d be surprised to see how far a simple non-DL model gets you.

I worked in Zillow’s AI team so I know both AI and real estate analytics problems.

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Ashraf_mahdy OP t1_j2e6lpq wrote

Can I dm you with more information maybe you're able to steer me in the right direction? If you're willing of course

I'm trying to do my due diligence before the start of the Module to be able to answer my teacher's questions effectively and know how deep I need to go

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psychorameses t1_j2e6yv6 wrote

Sure, I'm just playing Genshin Impact until work starts again anyway.

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