Mark Douthwaite markdouthwaite

## 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)

## Dropout.py
# -*- coding: utf-8 -*-

import sys
import numpy

numpy.seterr(all='ignore')


'''

## CATCH_Keras_RL.md

      
              3 files
            
          
              64 forks
            
          
              27 comments
            
          
              154 stars
            
          
                EderSantana
                / CATCH_Keras_RL.md
            
            
              Last active
              June 22, 2024 17:07
            
              
                Keras plays catch - a single file Reinforcement Learning example
              
          
    Code for Keras plays catch blog post
Train

python qlearn.py
Test


Generate figures


## AttentionWithContext.py
def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:
        x (): input
        kernel (): weights
    Returns:
    """
    if K.backend() == 'tensorflow':

## python_environment_setup.md

      
              1 file
            
          
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              37 stars
            
          
                Geoyi
                / python_environment_setup.md
            
            
              Created
              January 20, 2018 19:01
                — forked from wronk/python_environment_setup.md
            
              
                Setting up your python development environment (with pyenv, virtualenv, and virtualenvwrapper)
              
          
    Overview

When you're working on multiple coding projects, you might want a couple different version of Python and/or modules installed. That way you can keep each project in its own sandbox instead of trying to juggle multiple projects (each with different dependencies) on your system's version of Python. This intermediate guide covers one way to handle multiple Python versions and Python environments on your own (i.e., without a package manager like conda). See the Using the workflow section to view the end result.
Use cases


Working on 2+ projects that each have their own dependencies; e.g., a Python 2.7 project and a Python 3.6 project, or developing a module that needs to work across multiple versions of Python. It's not reasonable to uninstall/reinstall modules every time you want to switch environments.
If you want to execute code on the cloud, you can set up a Python environment that mirrors the relevant
	"""
	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)
	# -- coding: utf-8 --

	import sys
	import numpy

	numpy.seterr(all='ignore')


	'''
	def dot_product(x, kernel):
	"""
	Wrapper for dot product operation, in order to be compatible with both
	Theano and Tensorflow
	Args:
	x (): input
	kernel (): weights
	Returns:
	"""
	if K.backend() == 'tensorflow':