Benedict Neo 梁耀恩 benthecoder

## solution_train.csv

          
            date
            label

            
              a8c6911b
              N

            
              eebdce12
              N

            
              6fb420a6
              L

            
              3bf8b132
              N

## region_a_train.csv

          
            date
            avg.temp
            max.temp
            min.temp
            precipitation
            avg.wind.speed
            max.wind.speed
            max.wind.speed.dir
            max.inst.wind.speed
            max.inst.wind.speed.dir
            min.atmos.pressure

            
              229b70a3
              3.3
              10.2
              -2.4
              0
              2.9
              9.3
              W
              14.3
              W
              1015.1

            
              3134f4ff
              5.7
              13.7
              -2.9
              0
              3.6
              10.7
              W
              15.8
              W
              1011.3

            
              dbfaf910
              13.8
              20
              9
              0
              5.3
              9.4
              SW
              15.2
              W
              1004.2

            
              3aea0cf0
              11.4
              19.3
              5.8
              0
              4.2
              10.1
              SW
              20.6
              SW
              1001.7

            
              f0227f56
              2.4
              7.7
              0.3
              43.5
              0.9
              3.7
              SW
              5.7
              SW
              1003.5

## nlp-text-processing.py
# NLP text processing functions in Python

# -----------------------
# remove punctuation

import string
# print(string.punctuation) -> '!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~'

def remove_punc(s):
  '''

## cnn-pytorch.py
class Net(nn.Module):
    ''' Models a simple Convolutional Neural Network'''

    def __init__(self):
	''' initialize the network '''
        super(Net, self).__init__()
	# 3 input image channel, 6 output channels,
	# 5x5 square convolution kernel
        self.conv1 = nn.Conv2d(3, 6, 5)
	# Max pooling over a (2, 2) window

## Solution 1 elegant
function sumAll(arr) {
  var result = 0;
  for (let i=Math.min(...arr); i<=Math.max(...arr); i++){
    result+=i;
  }
  return result;
}

sumAll([1, 4]);

## Sum All Numbers in a Range solution 3
function sumAll(arr) {
  return (arr[0]+arr[1])*(Math.abs(arr[0]-arr[1])+1)/2;
}

## Sum All Numbers in a Range solution 1
function sumAll(arr) {
  var max = Math.max(...arr);
  var min = Math.min(...arr);
  var temp = 0;
  for(var i=min; i<=max; i++){
    temp += i;
    }
  return (temp);
}

## Sum All Numbers in a Range solution 2
function sumAll(arr) {
  const max = Math.max(...arr);
  const min = Math.min(...arr);
  return((min+max)*(max - min +1)/2);
}

console.log(sumAll([1,4]));
date	avg.temp	max.temp	min.temp	precipitation	avg.wind.speed	max.wind.speed	max.wind.speed.dir	max.inst.wind.speed	max.inst.wind.speed.dir	min.atmos.pressure
229b70a3	3.3	10.2	-2.4	0	2.9	9.3	W	14.3	W	1015.1
3134f4ff	5.7	13.7	-2.9	0	3.6	10.7	W	15.8	W	1011.3
dbfaf910	13.8	20	9	0	5.3	9.4	SW	15.2	W	1004.2
3aea0cf0	11.4	19.3	5.8	0	4.2	10.1	SW	20.6	SW	1001.7
f0227f56	2.4	7.7	0.3	43.5	0.9	3.7	SW	5.7	SW	1003.5
	# NLP text processing functions in Python

	# -----------------------
	# remove punctuation

	import string
	# print(string.punctuation) -> '!"#$%&\'()*+,-./:;<=>?@[\\]^_`{\|}~'

	def remove_punc(s):
	'''
	class Net(nn.Module):
	''' Models a simple Convolutional Neural Network'''

	def __init__(self):
	''' initialize the network '''
	super(Net, self).__init__()
	# 3 input image channel, 6 output channels,
	# 5x5 square convolution kernel
	self.conv1 = nn.Conv2d(3, 6, 5)
	# Max pooling over a (2, 2) window
	function sumAll(arr) {
	var result = 0;
	for (let i=Math.min(...arr); i<=Math.max(...arr); i++){
	result+=i;
	}
	return result;
	}

	sumAll([1, 4]);
	function sumAll(arr) {
	return (arr[0]+arr[1])*(Math.abs(arr[0]-arr[1])+1)/2;
	}
	function sumAll(arr) {
	var max = Math.max(...arr);
	var min = Math.min(...arr);
	var temp = 0;
	for(var i=min; i<=max; i++){
	temp += i;
	}
	return (temp);
	}
	function sumAll(arr) {
	const max = Math.max(...arr);
	const min = Math.min(...arr);
	return((min+max)*(max - min +1)/2);
	}

	console.log(sumAll([1,4]));