Machine Learning Homework
It’s like if you had a video of a guy falling down the stairs and you wanted to train a neural network to classify what happens in the video.A regular neural network might be able to tell that the guy was standing up in the first frame of the video.So now I need to salvage my average, the two things I can do are: The second option sounds a lot cooler at this point.I’ve learned a bit about neural networks before, you can check out my article on Convolutional Neural Networks for image recognition or my article on applying CNNs to classify skin lesions.The neural network does a forward pass and then on the second forward pass, it takes in some of the information from the first iteration to get more context to make the second prediction. We use this new type of network to operate over sequences of data in a much better way than what we could do with traditional networks.But one problem with RNNs is the vanishing/exploding gradient problem.
We can train a neural network on a bunch of different essays and perform sampling on the model to generate a new essay we’ve never seen before!
It contains a bunch of mathematical formulas that helps RNNs solve the vanishing gradient problem and also makes predictions more accurate.
When working with an LSTM, think of there being four pieces of information: long term memory, short term memory, an event and an output.
Maybe it’s the fact that assignments are always super subjective.
Maybe it’s because the books that we’re forced to read are long and boring.