#A Collection of NLP notes
##N-grams
###Calculating unigram probabilities:
P( wi ) = count ( wi ) ) / count ( total number of words )
In english..
#!/bin/bash | |
############################################### | |
# To use: | |
# https://raw.github.com/gist/2776351/??? | |
# chmod 777 install_postgresql.sh | |
# ./install_postgresql.sh | |
############################################### | |
echo "*****************************************" | |
echo " Installing PostgreSQL" | |
echo "*****************************************" |
#A Collection of NLP notes
##N-grams
###Calculating unigram probabilities:
P( wi ) = count ( wi ) ) / count ( total number of words )
In english..
#!/bin/bash | |
# Sometimes you need to move your existing git repository | |
# to a new remote repository (/new remote origin). | |
# Here are a simple and quick steps that does exactly this. | |
# | |
# Let's assume we call "old repo" the repository you wish | |
# to move, and "new repo" the one you wish to move to. | |
# | |
### Step 1. Make sure you have a local copy of all "old repo" | |
### branches and tags. |
This was tested on a ThinkPad P70 laptop with an Intel integrated graphics and an NVIDIA GPU:
lspci | egrep 'VGA|3D'
00:02.0 VGA compatible controller: Intel Corporation Device 191b (rev 06)
01:00.0 VGA compatible controller: NVIDIA Corporation GM204GLM [Quadro M3000M] (rev a1)
A reason to use the integrated graphics for display is if installing the NVIDIA drivers causes the display to stop working properly.
In my case, Ubuntu would get stuck in a login loop after installing the NVIDIA drivers.
This happened regardless if I installed the drivers from the "Additional Drivers" tab in "System Settings" or the ppa:graphics-drivers/ppa
in the command-line.
from bs4 import BeautifulSoup | |
import requests | |
import re | |
import urllib2 | |
import os | |
import argparse | |
import sys | |
import json | |
# adapted from http://stackoverflow.com/questions/20716842/python-download-images-from-google-image-search |
from sklearn.feature_extraction.text import CountVectorizer | |
import numpy as np | |
import pandas as pd | |
import scipy as sp | |
posts = pd.read_csv('posts.csv') | |
# Create vectorizer for function to use | |
vectorizer = CountVectorizer(binary=False) | |
y = posts["score"].values.astype(np.float32) |
#!/bin/bash | |
#### Restart Bluetooth | |
if [ "$1" == "resetBT" ] ; then | |
sudo rfkill block bluetooth && sleep 0.1 && sudo rfkill unblock bluetooth; | |
exit; | |
fi; | |
#### Toggle listen/speak | |
if [ "$1" == "" -o "$1" == "toggle" ] ; then |
This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of