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Use (most) macOS style keyboard shortcuts on Windows

Make Windows PC's shortcut act like macOS (Mac OS X)

With this AutoHotKey script, you can use most macOS style shortcuts (eg, cmd+c, cmd+v, ...) on Windows with a standard PC keyboard.

Note that:

1. you shouldn't change the modifier keys mapping with keyboard DIP. This script assumes you use a standard PC keyboard layout, and wish to use shortcuts as if it was a mac keyboard layout.
2. To use cmd + shift + ↑ / ↓ / ← / → (select text between cursor and top / bottom / beginning of line / end of line), You should disable the Between input languages shotcut from Control Panel\Clock, Language, and Region\Language\Advanced settings > Change lanugage bar hot keys due to conflicting.

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Build tensorflow on macOS with NVIDIA CUDA support (GPU acceleration)

Reference:

• Official instruction Install Tensorflow from source
• smitshilu/Tensorflow_Build_GPU.md

Software	version
Tensorflow	1.5

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********************************
Gist
********************************

Motivation
-----------
The typical mapreduce job creates files with the prefix "part-"..and then the "m" or "r" depending
on whether it is a map or a reduce output, and then the part number.  There are scenarios where we
may want to create separate files based on criteria-data keys and/or values.  Enter the "MultipleOutputs" 
functionality.

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SLIDES := $(patsubst %.md,%.slides.pdf,$(wildcard *.md))
HANDOUTS := $(patsubst %.md,%.handout.pdf,$(wildcard *.md))

all : $(SLIDES)

%.slides.pdf : %.md
	pandoc --latex-engine=xelatex --toc $^ -t beamer --slide-level 2 -o $@

%.handout.pdf : %.md
	pandoc $^ -t beamer --slide-level 2 -V handout -o $@

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import numpy as np
from math import exp, log

"""
SGD for logistic loss + factorization machines
The code follows this paper:
[1] http://www.ics.uci.edu/~smyth/courses/cs277/papers/factorization_machines_with_libFM.pdf
"""

def sigmoid(x):

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import numpy as np
from matplotlib import pylab as plt
#from mpltools import style # uncomment for prettier plots
#style.use(['ggplot'])

'''
function definitions
'''
# generate all bernoulli rewards ahead of time
def generate_bernoulli_bandit_data(num_samples,K):

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########################### GTEST
# Enable ExternalProject CMake module
INCLUDE(ExternalProject)

# Set default ExternalProject root directory
SET_DIRECTORY_PROPERTIES(PROPERTIES EP_PREFIX ${CMAKE_BINARY_DIR}/third_party)

# Add gtest
# http://stackoverflow.com/questions/9689183/cmake-googletest
ExternalProject_Add(

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Introduction to Kafka

Kafka acts as a kind of write-ahead log (WAL) that records messages to a persistent store (disk) and allows subscribers to read and apply these changes to their own stores in a system appropriate time-frame.

Terminology:

• Producers send messages to brokers
• Consumers read messages from brokers
• Messages are sent to a topic

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"""
(C) Mathieu Blondel - 2010
License: BSD 3 clause

Implementation of the collapsed Gibbs sampler for
Latent Dirichlet Allocation, as described in

Finding scientifc topics (Griffiths and Steyvers)
"""