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class node { | |
value: any | |
left: any | |
right: any | |
height: number | |
balanceFactor(){ | |
var bf = (this.right.height) - (this.left.height); | |
} | |
constructor(v,h) { |
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'use strict'; | |
class example_component extends HTMLElement { | |
/* THIS RETURNS THE NAME OF OUR WEB COMPONENT */ | |
static get is() { | |
return 'v-graph' | |
} | |
/* WE CAN SET UP GETS TO RETRIEVE THE ELEMENT NAMES BAM, EASY ! */ |
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import tensorflow as tf | |
import numpy as np | |
def sigmoid(x): | |
return 1 / (1 + np.exp(-x)) | |
x_learn = np.array([[1.000,2.000], | |
[10.000,2.0000], | |
[9.000,3.0000], | |
[5.000,8.000], |
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function convertToIntArray(hex){ | |
var bytes = [], | |
str; | |
for(var i=0; i<hex.length-1;i+=2){ | |
bytes.push(parseInt(hex.substr(i, 2), 16)) | |
} |
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import numpy as np | |
inputs = np.array([[1],[100],[3],[30],[40]]) | |
testSet = np.array([[10],[13],[19],[33],[1]]) | |
outputs = np.array([[5],[203],[9],[63],[83]]) | |
bias = 1 | |
biasWeight = 1 | |
#initWeights | |
weights = np.random.random() |
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var curryAdd = (x) => (y) => return x + y; |
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