#A Collection of NLP notes
##N-grams
###Calculating unigram probabilities:
P( wi ) = count ( wi ) ) / count ( total number of words )
In english..
''' | |
Created on 2012. 2. 19. | |
This module is for playing mp3 (limited) and wav formatted audio file | |
@author: John | |
''' | |
import pygame | |
def playsound(soundfile): | |
"""Play sound through default mixer channel in blocking manner. | |
This will load the whole sound into memory before playback |
#A Collection of NLP notes
##N-grams
###Calculating unigram probabilities:
P( wi ) = count ( wi ) ) / count ( total number of words )
In english..
# (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 |
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 |
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 |
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 |
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 |
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: |