Yiqun Hu codingneo

## gist:1630790

      
              1 file
            
          
              118 forks
            
          
              47 comments
            
          
              1121 stars
            
          
                jimbojsb
                / gist:1630790
            
            
              Created
              January 18, 2012 03:52
            
              
                Code highlighting for Keynote presentations
              
          
    Step 0:

Get Homebrew installed on your mac if you don't already have it
Step 1:

Install highlight. "brew install highlight". (This brings down Lua and Boost as well)
Step 2:


## adam.py
"""
The MIT License (MIT)

Copyright (c) 2015 Alec Radford

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is

## digits.md

      
              1 file
            
          
              9 forks
            
          
              1 comment
            
          
              15 stars
            
          
                joyofdata
                / digits.md
            
            
              Last active
              February 2, 2020 02:28
            
              
                Installing CUDA, cuDNN, caffe and DIGITS on EC2
              
          
Preliminary Updates and Installations
(http://markus.com/install-theano-on-aws/)
sudo apt-get update

sudo apt-get -y dist-upgrade  


## min-char-rnn.py
"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)
	"""
	The MIT License (MIT)

	Copyright (c) 2015 Alec Radford

	Permission is hereby granted, free of charge, to any person obtaining a copy
	of this software and associated documentation files (the "Software"), to deal
	in the Software without restriction, including without limitation the rights
	to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
	copies of the Software, and to permit persons to whom the Software is
	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)