Fabian Schreiber fabsta

model setup

from numpy.random import random, permutation
from scipy import misc, ndimage
from scipy.ndimage.interpolation import zoom

import keras
from keras import backend as K
from keras.utils.data_utils import get_file
from keras.models import Sequential, Model

sorting files by user

ls -l | sort -k3,3

find ignore errors
find / -name livy_server 2>/dev/null

Metadata

#Selecting a database	
USE database;	USE database;

#Listing databases	
SHOW DATABASES;	SHOW DATABASES;

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Pure Python

Types

a = 2           # integer
b = 5.0         # float
c = 8.3e5       # exponential
d = 1.5 + 0.5j  # complex

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Preliminaries/Import

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from pandas import DataFrame, Series

Preliminaries

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
from pandas import DataFrame, Series

MATH

basic operations

10 + 4          # add (returns 14)
10 - 4          # subtract (returns 6)
10 * 4          # multiply (returns 40)
10 ** 4         # exponent (returns 10000)
10 / 4          # divide (returns 2 because both types are 'int')
10 / float(4) # divide (returns 2.5)

Exceptions

try - except

try:
    image_data = (ndimage.imread(image_file).astype(float) - 
                    pixel_depth / 2) / pixel_depth
      if image_data.shape != (image_size, image_size):
        raise Exception('Unexpected image shape: %s' % str(image_data.shape))
 dataset[num_images, :, :] = image_data


	# Hive
	```

	```

	# Oracle

	```
	val oracle_db = sqlContext.load("jdbc", Map("url" -> "jdbc:oracle:thin:user/passwd@//server.com:1526/serviceID.com", "dbtable" -> "table"))

	name := "Spark2.0-and-greater"

	version := "1.0"

	//Older Scala Version
	scalaVersion := "2.11.8"

	val overrideScalaVersion = "2.11.8"
	val sparkVersion = "2.0.0"
	val sparkXMLVersion = "0.3.3"