floriandotpy

#!/usr/bin/python3

from cnn import cnn
import hyperopt


def objective(args):

    params = cnn.ExperimentParameters()

dansileshi

import tensorflow as tf
import numpy as np

FC_SIZE = 1024
DTYPE = tf.float32


def _weight_variable(name, shape):
    return tf.get_variable(name, shape, DTYPE, tf.truncated_normal_initializer(stddev=0.1))

jkleint

#!/usr/bin/env python
"""
Example of using Keras to implement a 1D convolutional neural network (CNN) for timeseries prediction.
"""

from __future__ import print_function, division

import numpy as np
from keras.layers import Convolution1D, Dense, MaxPooling1D, Flatten
from keras.models import Sequential

hnykda

import pandas as pd  
from random import random

flow = (list(range(1,10,1)) + list(range(10,1,-1)))*100
pdata = pd.DataFrame({"a":flow, "b":flow})  
pdata.b = pdata.b.shift(9)  
data = pdata.iloc[10:] * random()  # some noise  

import numpy as np

binaryatrocity

from sys import argv
from base64 import b64encode
from datetime import datetime
from Crypto.Hash import SHA, HMAC

def create_signature(secret_key, string):
    """ Create the signed message from api_key and string_to_sign """
    string_to_sign = string.encode('utf-8')
    hmac = HMAC.new(secret_key, string_to_sign, SHA)
    return b64encode(hmac.hexdigest())

hrldcpr

One-line Tree in Python

Using Python's built-in defaultdict we can easily define a tree data structure:

def tree(): return defaultdict(tree)

That's it!