Kevin Mader kmader

Polyglot Data Science with IPython & friends

A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.

This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.

See the companion notebook for data preparation and setup.

AOE2HD - For Mac OSX

Estimated time: 10 minutes

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Installing PortingKit

Code for Keras plays catch blog post

Train

python qlearn.py

Test

Generate figures

	"""
	The most atomic way to train and inference a GPT in pure, dependency-free Python.
	This file is the complete algorithm.
	Everything else is just efficiency.

	@karpathy
	"""

	import os # os.path.exists
	import math # math.log, math.exp

	from functools import wraps
	from itertools import islice, tee, zip_longest, chain, product
	from collections import deque
	from pandas import DataFrame

	nwise = lambda g, , n=2: zip((islice(g, i, None) for i, g in enumerate(tee(g, n))))
	nwise_longest = lambda g, , n=2, fv=object(): zip_longest((islice(g, i, None) for i, g in enumerate(tee(g, n))), fillvalue=fv)
	first = lambda g, *, n=1: zip(chain(repeat(True, n), repeat(False)), g)
	last = lambda g, , m=1, s=object(): ((y[-1] is s, x) for x, y in nwise_longest(g, n=m+1, fv=s))

	"""Performs automatic speed edits to audio books.

	Example usage:

	Assuming you have an audiobook book.aax on your Desktop:

	1. Convert it to wav:
	ffmpeg -i ~/Desktop/book.aax ~/Desktop/book.wav

	2. Adjust the speed:

	from keras.layers.core import Layer
	import keras.backend as K

	if K.backend() == 'tensorflow':
	import tensorflow as tf
	def K_arange(start, stop=None, step=1, dtype='int32'):
	result = tf.range(start, limit=stop, delta=step, name='arange')
	if dtype != 'int32':
	result = K.cast(result, dtype)
	return result

	"""
	AWS Batch wrapper for Luigi

	From the AWS website:

	AWS Batch enables you to run batch computing workloads on the AWS Cloud.

	Batch computing is a common way for developers, scientists, and engineers
	to access large amounts of compute resources, and AWS Batch removes the
	undifferentiated heavy lifting of configuring and managing the required