Encoding Labels for Networks ๐ท๏ธ - Supervised Learning Prep ๐ - Topic 201 #ai #ml
Key Takeaways
The video discusses encoding labels for networks in supervised learning tasks, specifically for categorical data classification, using numeric values for mathematical operations during training.
Full Transcript
during a supervised learning task of training enal Network to classify categorical data we now know that we pass both the sample and its corresponding label to the network as input during training the network makes use of the label that was supplied as part of the input in order to calculate the loss between this true label and the output from the network when we discuss these labels we typically talk about them using the words that describe the category for which the given data belongs so for example we have this network here that is accepting this image of a dumbbell so the label for this image we would just refer to as dumbbell and similarly the network outputs between the two classes of dumbbell and kettlebell but actually even though we refer to the labels in these ways when we pass the data to the network the labels actually become encoded into numeric values so actually over here in this input we can see that dumbbell has been encoded into the value zero for example the network needs these labels to be encoded into numeric values since there will be mathematical operations occurring with these labels during the training process
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