cbaziotis

def dot_product(x, kernel):
    """
    Wrapper for dot product operation, in order to be compatible with both
    Theano and Tensorflow
    Args:
        x (): input
        kernel (): weights
    Returns:
    """
    if K.backend() == 'tensorflow':

jbochi

KevinLiao159

from pyspark.ml.recommendation import ALS


def tune_ALS(train_data, validation_data, maxIter, regParams, ranks):
    """
    grid search function to select the best model based on RMSE of
    validation data

    Parameters
    ----------

grantcooksey

import io
import json
import botocore.session
from botocore.stub import Stubber
from botocore.response import StreamingBody


expected_message = {
    'message': 'readme'
}

GenevieveBuckley

from io import StringIO


def double():
    x = input("Enter an integer: ")
    return int(x) * 2


def adding():
    x = float(input('Enter the first number'))