Tariq Hassan TariqAHassan

## sinc_interp.m
% From http://phaseportrait.blogspot.com/2008/06/sinc-interpolation-in-matlab.html

% Ideally "resamples" x vector from s to u by sinc interpolation
function y = sinc_interp(x,s,u)
    % Interpolates x sampled sampled at "s" instants
    % Output y is sampled at "u" instants ("u" for "upsampled")
    % (EXPECTS x, s, and u to be ROW VECTORS!!)

    % Find the period of the undersampled signal
    T = s(2)-s(1);

## gist:1483052
<!DOCTYPE html>
<html>
  <head>
    <script type="text/javascript" src="http://mbostock.github.com/d3/d3.js?1.27.1"></script>
    <style type="text/css">

div.tooltip {
  position: absolute;
  text-align: center;
  width: 120px;

## gist:e2dd904bd648b0bd4554
#!/usr/bin/env sh

# checks to see if running
launchctl list | grep elasticsearch

launchctl unload ~/Library/LaunchAgents/homebrew.mxcl.elasticsearch.plist
launchctl remove homebrew.mxcl.elasticsearch

pkill -f elasticsearch

## ApacheHadoop_NativeLibs.adoc

      
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                zedar
                / ApacheHadoop_NativeLibs.adoc
            
            
              Last active
              August 13, 2020 00:59
            
              
                Add native libraries to Apache Hadoop installation
              
          
    Apache Hadoop - add native libraries


If native libraries are not available the following message is displayed with every hadoop command: hadoop checknative


WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable


Clone hadoop source code


## Build tensorflow on OSX with NVIDIA CUDA support.md

      
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                ageitgey
                / Build tensorflow on OSX with NVIDIA CUDA support.md
            
            
              Last active
              September 11, 2023 13:08
            
          
    Build tensorflow on OSX with NVIDIA CUDA support (GPU acceleration)

These instructions are based on Mistobaan's
gist
but expanded and updated to work with the
latest tensorflow OSX CUDA PR.
Requirements

OS X 10.10 (Yosemite) or newer


## git-deployment.md

      
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                noelboss
                / git-deployment.md
            
            
              Last active
              July 16, 2024 09:50
            
              
                Simple automated GIT Deployment using Hooks
              
          
    Simple automated GIT Deployment using GIT Hooks

Here are the simple steps needed to create a deployment from your local GIT repository to a server based on this in-depth
tutorial.
How it works

You are developing in a working-copy on your local machine, lets say on the master branch. Most of the time, people would push code to a remote
server like github.com or gitlab.com and pull or export it to a production server. Or you use a service like deepl.io to act upon a Web-Hook that's triggered that service.

  
## keras_bidirectional_tagger.py
# Keras==1.0.6
from keras.models import Sequential
import numpy as np
from keras.layers.recurrent import LSTM
from keras.layers.core import TimeDistributedDense, Activation
from keras.preprocessing.sequence import pad_sequences
from keras.layers.embeddings import Embedding
from sklearn.cross_validation import train_test_split
from keras.layers import Merge
from keras.backend import tf

## private_fork.md

      
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                0xjac
                / private_fork.md
            
            
              Last active
              July 28, 2024 14:13
            
              
                Create a private fork of a public repository
              
          
    The repository for the assignment is public and Github does not allow the creation of private forks for public repositories.
The correct way of creating a private frok by duplicating the repo is documented here.
For this assignment the commands are:

Create a bare clone of the repository.
(This is temporary and will be removed so just do it wherever.)


git clone --bare git@github.com:usi-systems/easytrace.git

  
## client.py
"""Creates a python socket client that will interact with javascript."""
import socket

socket_path = '/tmp/node-python-sock'
# connect to the unix local socket with a stream type
client = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
client.connect(socket_path)
# send an initial message (as bytes)
client.send(b'python connected')
# start a loop

## example.py
#!/usr/bin/env python3
# -*- coding: UTF-8 -*-

import socket
import json

server_address = '/tmp/example.sock'

sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
sock.connect(server_address)
	% From http://phaseportrait.blogspot.com/2008/06/sinc-interpolation-in-matlab.html

	% Ideally "resamples" x vector from s to u by sinc interpolation
	function y = sinc_interp(x,s,u)
	% Interpolates x sampled sampled at "s" instants
	% Output y is sampled at "u" instants ("u" for "upsampled")
	% (EXPECTS x, s, and u to be ROW VECTORS!!)

	% Find the period of the undersampled signal
	T = s(2)-s(1);
	<!DOCTYPE html>
	<html>
	<head>
	<script type="text/javascript" src="http://mbostock.github.com/d3/d3.js?1.27.1"></script>
	<style type="text/css">

	div.tooltip {
	position: absolute;
	text-align: center;
	width: 120px;
	#!/usr/bin/env sh

	# checks to see if running
	launchctl list \| grep elasticsearch

	launchctl unload ~/Library/LaunchAgents/homebrew.mxcl.elasticsearch.plist
	launchctl remove homebrew.mxcl.elasticsearch

	pkill -f elasticsearch
	# Keras==1.0.6
	from keras.models import Sequential
	import numpy as np
	from keras.layers.recurrent import LSTM
	from keras.layers.core import TimeDistributedDense, Activation
	from keras.preprocessing.sequence import pad_sequences
	from keras.layers.embeddings import Embedding
	from sklearn.cross_validation import train_test_split
	from keras.layers import Merge
	from keras.backend import tf
	"""Creates a python socket client that will interact with javascript."""
	import socket

	socket_path = '/tmp/node-python-sock'
	# connect to the unix local socket with a stream type
	client = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
	client.connect(socket_path)
	# send an initial message (as bytes)
	client.send(b'python connected')
	# start a loop
	#!/usr/bin/env python3
	# -- coding: UTF-8 --

	import socket
	import json

	server_address = '/tmp/example.sock'

	sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
	sock.connect(server_address)