It’s there to help you label a dataset, so yes, you can have the labels you want.
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I was part of the fellowship this past summer some of my fellow fellows built this! Pretty cool to see it live!
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Does platform.ai employ active learning ?
The projections that Jeremy was demonstrating a couple of min back – are they some intermediate layer taken from a trained network or similar?
Or is this a standalone tool which just takes all images, similar to doing PCA on a high-dimensional data. ?
It involves taking intermediate layers from a network.
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Yes it is.
Does adding many more features always positive for a neural net, or can it lead to a kind of “information overflow” and actually be detrimental to the model ?
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Making life easier for your model will generally result in getting better results.
That being said, to quote last-week-Jeremy, try bla 
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It is always positive as long as the information is relevant and you regularize accordingly.
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Don’t all these date parts add a ton of co-linearity among features?
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Do you have any advice for combining image data with tabular data?
For example, say you have images of stores, and you also have tabular information about those stores like their locations’ coordinates.
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Co-linearity isn’t really a problem, in that you are not trying to get a model with the fewest features, but rather just to make accurate predictions.
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Categorify is a fastai specific feature, or is part of pandas itself ?
It’s a processor of fastai.
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Would explaining fastai processors be part of this or an advanced discussion?
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He answered that question in lesson 4 (not 100% sure). But what you do is have two model and combine them. He answered this for combining NLP tokenized data with metadata
Processors in general is advanced. If you have a question on any of the ones Jeremy is explaining right now, go ahead!
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Is day 365 that much different from day 1 of next year? But on this scale it will be.
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One thing Jeremy didn’t say with FillNA is that it only makes modifications on continuous variables. On categorical variables, the NaNs have a special code (-1) so we don’t need to create a new column for them.
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Ok, my questions are more in general and how everything is handled going through the parameters. I will put it in a new post if I still have answers after this lecture.