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# Taewoo Leeoiehot

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Created Apr 23, 2017
ES6 Features
View es6.js
 // // ES6 Features // // 원본: http://es6-features.org // // 1. 상수 // ======= const PI = 3.141593
Created Apr 9, 2017
오차역전파법을 위한 Relu층, Sigmoid층
View pydl_backpropagation_layer2.py
 import numpy as np ''' class ReluLayer: def __init__(self): self.x = None def forward(self, x): self.x = x if x > 0: return x
Created Apr 8, 2017
오차역전파법을 위한 덧셈층, 곱셈층
View pydl_backpropagation_layer1.py
 class AddLayer: def __init__(self): pass def forward(self, x, y): return x + y def backward(self, dout): dx = dout * 1 dy = dout * 1 return dx, dy
Created Mar 18, 2017
mnist, 순전파, 2층 신경망 학습시키기
View pydl_mnist_train.py
 import sys, os sys.path.append(os.pardir) import numpy as np from common.functions import * from common.gradient import * from dataset.mnist import load_mnist class TwoLayerNet: def __init__(self, inputSize, hiddenSize, outputSize, weight=0.01): self.w1 = weight * np.random.randn(inputSize, hiddenSize)
Created Mar 11, 2017
머신러닝, 수치미분, 편미분, 기울기, 경사하강법
 # 머신러닝, 수치 미분, 편미분, 기울기gradient, 경사 하강법gradient descent # 수치 미분numerical differentiation, 전방 차분 def numerical_diff_bad(f, x): h = 10e-50 # np.float32(1e-50) => 0.0, 반올림 오차 문제. return (f(x+h) - f(x)) / h # 수치 미분, 중심 차분 def numerical_diff(f, x): h = 1e-4 # 0.0001
Last active Feb 24, 2017
마야에서 Edge의 Normal, Crease, ArnoldSubdiv을 동시에 설정하기
View maya_subdiv.mel
 // 0: Smooth // 1: Jelly // 2: Round Rect 1 // 3: Round Rect 2 // 4: Bevel // 5: Hard global proc TZ_Subdiv_SetLevel(int \$level) { int \$minSubdivLevel = max(5, \$level); // 최저 Subdiv레벨: 5
Last active Feb 24, 2017
마야, 회전축 복사하기
View maya_copyPivot.mel
 global proc TZ_Transform_CopyPivot(string \$src, string \$dest) { float \$scalePivot[3]; float \$rotatePivot[3]; \$scalePivot = `xform -query -worldSpace -scalePivot \$src`; \$rotatePivot = `xform -query -worldSpace -rotatePivot \$src`; xform -worldSpace -scalePivot \$scalePivot[0] \$scalePivot[1] \$scalePivot[2] \$dest; xform -worldSpace -rotatePivot \$rotatePivot[0] \$rotatePivot[1] \$rotatePivot[2] \$dest; }
Last active Feb 19, 2017
MNIST, 이미 학습된 신경망을 사용해서 숫자 이미지를 추론하기
View pydl_neuralnet_mnist.py
 import sys, os import numpy as np import pickle import random from PIL import Image # https://github.com/oreilly-japan/deep-learning-from-scratch/common, dataset sys.path.append(os.pardir) from dataset.mnist import load_mnist from common.functions import sigmoid, softmax
Last active Feb 19, 2017
평가함수, 평균제곱오차 & 교차엔트로피오차
View pydl_costfuncs.py
 import sys, os import numpy as np # 정답표, One hot label t = np.array([ [0,0,1,0,0,0,0,0,0,0], # 2 [0,0,0,1,0,0,0,0,0,0], # 3 [0,0,0,0,0,1,0,0,0,0], # 5 [1,0,0,0,0,0,0,0,0,0], # 0 [0,1,0,0,0,0,0,0,0,0] # 1
Last active Feb 18, 2017
View sketchup_exportFbx.rb
 def exportFbx(filename) if Sketchup.open_file(filename) then model = Sketchup.active_model dir = File.dirname(filename) basename = File.basename(filename,'.*') #model.save_thumbnail "#{dir}/#{basename}.png" model.export "#{dir}/#{basename}.fbx", false else puts "Failed to Load fbx." end
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