Hongjoo Lee midnightradio

## XPS-15 9560 Getting Nvidia To Work on KDE Neon
# As of writing this, 4.11 kernel fails, 4.10.15 fails, 4.11rc8 seems to be working. Apply the graphics patches first.

# Install Intel Graphics Patch Firmwares (This should reboot your system):
bash -c "$(curl -fsSL http://bit.ly/IGFWL-install)"

# Update to 4.11.2 kernel. nvidia-375 compiles fine >=4.11.1
cd /tmp
wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-headers-4.11.2-041102_4.11.2-041102.201705201036_all.deb
wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-headers-4.11.2-041102-generic_4.11.2-041102.201705201036_amd64.deb
wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-image-4.11.2-041102-generic_4.11.2-041102.201705201036_amd64.deb

## XPS-15 9560 Getting Nvidia To Work on KDE Neon
# As of writing this, 4.11 kernel fails, 4.10.15 fails, 4.11rc8 seems to be working. Apply the graphics patches first.

# Install Intel Graphics Patch Firmwares (This should reboot your system):
bash -c "$(curl -fsSL http://bit.ly/IGFWL-install)"

# Update to 4.11.2 kernel. nvidia-375 compiles fine >=4.11.1
cd /tmp
wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-headers-4.11.2-041102_4.11.2-041102.201705201036_all.deb
wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-headers-4.11.2-041102-generic_4.11.2-041102.201705201036_amd64.deb
wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-image-4.11.2-041102-generic_4.11.2-041102.201705201036_amd64.deb

## install-tensorflow.sh
# Note – this is not a bash script (some of the steps require reboot)
# I named it .sh just so Github does correct syntax highlighting.
#
# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
#
# The CUDA part is mostly based on this excellent blog post:
# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

# Install various packages
sudo apt-get update

## useful_pandas_snippets.py
#List unique values in a DataFrame column
pd.unique(df.column_name.ravel())

#Convert Series datatype to numeric, getting rid of any non-numeric values
df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

#Grab DataFrame rows where column has certain values
valuelist = ['value1', 'value2', 'value3']
df = df[df.column.isin(value_list)]

## jira-precommit.sh
#!/bin/sh -x
## REST API JIRA KEY check

#List of projects that do not require strict JIRA KEY commits
#list in space and case-insensitive
NON_STRICT="sports"


# Authentication credentials
username=root

## inflate.py
#!/usr/bin/env python
# coding: utf-8

from __future__ import unicode_literals, print_function
import sys, zipfile, shutil, os, fileinput

def inflate(filename):
    print(filename)
    zfile = zipfile.ZipFile(filename)
    for f in zfile.namelist():

## cluster_example.py
import sys

import numpy
from nltk.cluster import KMeansClusterer, GAAClusterer, euclidean_distance
import nltk.corpus
from nltk import decorators
import nltk.stem

stemmer_func = nltk.stem.snowball.EnglishStemmer().stem
stopwords = set(nltk.corpus.stopwords.words('english'))
	# As of writing this, 4.11 kernel fails, 4.10.15 fails, 4.11rc8 seems to be working. Apply the graphics patches first.

	# Install Intel Graphics Patch Firmwares (This should reboot your system):
	bash -c "$(curl -fsSL http://bit.ly/IGFWL-install)"

	# Update to 4.11.2 kernel. nvidia-375 compiles fine >=4.11.1
	cd /tmp
	wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-headers-4.11.2-041102_4.11.2-041102.201705201036_all.deb
	wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-headers-4.11.2-041102-generic_4.11.2-041102.201705201036_amd64.deb
	wget http://kernel.ubuntu.com/~kernel-ppa/mainline/v4.11.2/linux-image-4.11.2-041102-generic_4.11.2-041102.201705201036_amd64.deb
	# Note – this is not a bash script (some of the steps require reboot)
	# I named it .sh just so Github does correct syntax highlighting.
	#
	# This is also available as an AMI in us-east-1 (virginia): ami-cf5028a5
	#
	# The CUDA part is mostly based on this excellent blog post:
	# http://tleyden.github.io/blog/2014/10/25/cuda-6-dot-5-on-aws-gpu-instance-running-ubuntu-14-dot-04/

	# Install various packages
	sudo apt-get update
	#List unique values in a DataFrame column
	pd.unique(df.column_name.ravel())

	#Convert Series datatype to numeric, getting rid of any non-numeric values
	df['col'] = df['col'].astype(str).convert_objects(convert_numeric=True)

	#Grab DataFrame rows where column has certain values
	valuelist = ['value1', 'value2', 'value3']
	df = df[df.column.isin(value_list)]
	#!/bin/sh -x
	## REST API JIRA KEY check

	#List of projects that do not require strict JIRA KEY commits
	#list in space and case-insensitive
	NON_STRICT="sports"


	# Authentication credentials
	username=root
	#!/usr/bin/env python
	# coding: utf-8

	from __future__ import unicode_literals, print_function
	import sys, zipfile, shutil, os, fileinput

	def inflate(filename):
	print(filename)
	zfile = zipfile.ZipFile(filename)
	for f in zfile.namelist():
	import sys

	import numpy
	from nltk.cluster import KMeansClusterer, GAAClusterer, euclidean_distance
	import nltk.corpus
	from nltk import decorators
	import nltk.stem

	stemmer_func = nltk.stem.snowball.EnglishStemmer().stem
	stopwords = set(nltk.corpus.stopwords.words('english'))