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Studying for a Tech Interview Sucks, so Here's a Cheat Sheet to Help

This list is meant to be a both a quick guide and reference for further research into these topics. It's basically a summary of that comp sci course you never took or forgot about, so there's no way it can cover everything in depth. It also will be available as a gist on Github for everyone to edit and add to.

Data Structure Basics

###Array ####Definition:

• Stores data elements based on an sequential, most commonly 0 based, index.
• Based on tuples from set theory.

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class Model(nn.Module):
    '''
    Some Model, in this case a convolution single layer
    '''
    def __init__(self, in_channels, out_channels, kernel_size):
        super(Model, self).__init__()
        self.conv2d = nn.Conv2d(in_channels, out_channels, kernel_size)
		
        # Initialize weights
        for m in self.modules():

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def pytorch_count_params(model):
  "count number trainable parameters in a pytorch model"
  total_params = sum(reduce( lambda a, b: a*b, x.size()) for x in model.parameters())
  return total_params