Ehsan Azar dashesy

## test_nccl.c
// Code from http://docs.nvidia.com/deeplearning/sdk/nccl-developer-guide/index.html#onedevprothrd

#define _BSD_SOURCE

#include <stdio.h>
#include "cuda_runtime.h"
#include "nccl.h"
#include "mpi.h"
#include <stdint.h>
#include <stdlib.h>

## ipython-notebook.service
# README:
# Copy this file to /usr/lib/systemd/system/
# sudo systemctl daemon-reload
# systemctl enable ipython-notebook
# systemctl start ipython-notebook
# The WorkingDirectory and ipython-dir must exist
# If you don't want anything fancy, go to http://127.0.0.1:8888 to see your notebook
# wheneber you want it

[Unit]

## joint_classifier.py
'''
Created on June 26, 2013

@author: dashesy

Purpose: Like FeatureUnion but can apply different X,y to different transformers
         Each transformer could accept different number os samples or features
         but the result should be concatenatable

'''

## joint_classifier.py
'''
Created on June 26, 2013

@author: dashesy

Purpose: glue the classifier wire logic to have multiple
         classifiers work jointly with different groups of X,y
         Each group could accept different number os samples or features

'''

## kernel_pca.py
"""Kernel Principal Components Analysis"""

# Author: Mathieu Blondel <mathieu@mblondel.org>
# License: BSD Style.

import numpy as np
from scipy import linalg

from ..utils.arpack import eigsh
from ..base import BaseEstimator, TransformerMixin

## gist:5577051
"""
Gaussian Mixture Models.

This implementation corresponds to frequentist (non-Bayesian) formulation
of Gaussian Mixture Models.
"""

# Author: Ron Weiss <ronweiss@gmail.com>
#         Fabian Pedregosa <fabian.pedregosa@inria.fr>
#         Bertrand Thirion <bertrand.thirion@inria.fr>
	// Code from http://docs.nvidia.com/deeplearning/sdk/nccl-developer-guide/index.html#onedevprothrd

	#define _BSD_SOURCE

	#include <stdio.h>
	#include "cuda_runtime.h"
	#include "nccl.h"
	#include "mpi.h"
	#include <stdint.h>
	#include <stdlib.h>
	# README:
	# Copy this file to /usr/lib/systemd/system/
	# sudo systemctl daemon-reload
	# systemctl enable ipython-notebook
	# systemctl start ipython-notebook
	# The WorkingDirectory and ipython-dir must exist
	# If you don't want anything fancy, go to http://127.0.0.1:8888 to see your notebook
	# wheneber you want it

	[Unit]
	'''
	Created on June 26, 2013

	@author: dashesy

	Purpose: Like FeatureUnion but can apply different X,y to different transformers
	Each transformer could accept different number os samples or features
	but the result should be concatenatable

	'''
	'''
	Created on June 26, 2013

	@author: dashesy

	Purpose: glue the classifier wire logic to have multiple
	classifiers work jointly with different groups of X,y
	Each group could accept different number os samples or features

	'''
	"""Kernel Principal Components Analysis"""

	# Author: Mathieu Blondel <mathieu@mblondel.org>
	# License: BSD Style.

	import numpy as np
	from scipy import linalg

	from ..utils.arpack import eigsh
	from ..base import BaseEstimator, TransformerMixin
	"""
	Gaussian Mixture Models.

	This implementation corresponds to frequentist (non-Bayesian) formulation
	of Gaussian Mixture Models.
	"""

	# Author: Ron Weiss <ronweiss@gmail.com>
	# Fabian Pedregosa <fabian.pedregosa@inria.fr>
	# Bertrand Thirion <bertrand.thirion@inria.fr>