lyastro

install Tensorflow with GPU support on Centos 7

system: fully installed Centos 7

• system update

$ sudo yum -y update
$ sudo yum -y install epel-release
$ sudo yum -y install gcc gcc-c++ python-pip python-devel atlas atlas-devel gcc-gfortran openssl-devel libffi-devel

aunyks

from flask import Flask
from flask import request
import json
import requests
import hashlib as hasher
import datetime as date
node = Flask(__name__)

# Define what a Snakecoin block is
class Block:

aunyks

import hashlib as hasher
import datetime as date

# Define what a Snakecoin block is
class Block:
  def __init__(self, index, timestamp, data, previous_hash):
    self.index = index
    self.timestamp = timestamp
    self.data = data
    self.previous_hash = previous_hash

oarriaga

from keras.layers.core import Layer
import keras.backend as K

if K.backend() == 'tensorflow':
    import tensorflow as tf
    def K_arange(start, stop=None, step=1, dtype='int32'):
        result = tf.range(start, limit=stop, delta=step, name='arange')
        if dtype != 'int32':
            result = K.cast(result, dtype)
        return result

aparrish

prakashjayy

from keras import applications
from keras.preprocessing.image import ImageDataGenerator
from keras import optimizers
from keras.models import Sequential, Model 
from keras.layers import Dropout, Flatten, Dense, GlobalAveragePooling2D
from keras import backend as k 
from keras.callbacks import ModelCheckpoint, LearningRateScheduler, TensorBoard, EarlyStopping

img_width, img_height = 256, 256

Vestride

Encoding Video

Installing

Install FFmpeg with homebrew. You'll need to install it with a couple flags for webm and the AAC audio codec.

brew install ffmpeg --with-libvpx --with-libvorbis --with-fdk-aac --with-opus

miguelmalvarez

import pandas as pd
import numpy as np
import logging
import time
import datetime
from sklearn.ensemble import RandomForestClassifier
from sklearn import cross_validation
from sklearn.svm import SVC
from sklearn.metrics import accuracy_score
from sklearn.feature_selection import VarianceThreshold

kastnerkyle

# (C) Kyle Kastner, June 2014
# License: BSD 3 clause

import scipy.stats as st
import numpy as np

class gmmhmm:
    #This class converted with modifications from https://code.google.com/p/hmm-speech-recognition/source/browse/Word.m
    def __init__(self, n_states):
        self.n_states = n_states

ttezel

#A Collection of NLP notes

##N-grams

###Calculating unigram probabilities:

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

In english..