What's a ML problem you are interested in but for which you haven't found a good tutorial / introduction?
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Preferably a *task* rather than a *technique* (what you are trying to do vs. how you are trying to do it). Too many people jump to tools that may be far from optimal when simpler, better solutions exist
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Also, if you are working with a specific dataset, please describe it
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Lots of excellent ideas in this thread! Thanks to everyone who's contributing :)
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Online learning
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Would be interesting to see in a tutorial different ways to cheat a neuronal net and how to prevent that. Havent done research if smt like that is outhttps://towardsdatascience.com/breaking-neural-networks-with-adversarial-attacks-f4290a9a45aa …
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Take a look at ML security
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I have a huge database of objects with string names (and - sometimes - other metadata). During inference, an unknown object comes in, denoted by its string name (in slight variations) and - sometimes - bit of metadata. /1
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Now I want to match the incoming object to the correct object in my database without comparing it with every single object in the database. I also want to know when such a match does not exist. How do I ideally structure this problem setup? I can use non-ML tools. /2
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am training a machine to learn to draw art from line sketches from the scratch.. Am using Google datasets called quick draw
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to train the model from scratch but the output has not improved.. What model can u i use apart from the RNNs and LSTM by Google?
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