trungkak

# 1. Install CUDA
# Preparation
sudo apt-get update
sudo apt-get upgrade
sudo apt-get install tmux build-essential gcc g++ make binutils
sudo apt-get install software-properties-common

# Download Cuda toolkit (Nvidia driver included)
cd ~/Downloads
# Download CUDA 8.0 from this https://developer.nvidia.com/cuda-80-ga2-download-archive, not 9.0

smddzcy

    private static class Vertex {
        private int uniqueLabel;

        public Vertex(int uniqueLabel) {
            super();
            this.uniqueLabel = uniqueLabel;
        }

        @Override
        public boolean equals(Object obj) {

pannous

"""Sequence-to-sequence model with an attention mechanism."""
# see https://www.tensorflow.org/versions/r0.10/tutorials/seq2seq/index.html
# compare https://github.com/tflearn/tflearn/blob/master/examples/nlp/seq2seq_example.py
from __future__ import print_function
import numpy as np
import tensorflow as tf

vocab_size=256 # We are lazy, so we avoid fency mapping and just use one *class* per character/byte
target_vocab_size=vocab_size
learning_rate=0.1

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

thotmx

$ sudo apt-get install chromium-chromedriver
$ sudo ln -s /usr/lib/chromium-browser/chromedriver /usr/bin/chromedriver

julionc

How to install PhantomJS on Ubuntu

Version: 1.9.8

Platform: x86_64

First, install or update to the latest system software.

sudo apt-get update
sudo apt-get install build-essential chrpath libssl-dev libxft-dev

ttezel

#A Collection of NLP notes

##N-grams

###Calculating unigram probabilities:

P( w_i ) = count ( w_i ) ) / count ( total number of words )

In english..