classification

# Lab 5 Logistic Regression Classifier import tensorflow as tf tf.set_random_seed(777) # for reproducibility x_data = [[1, 2], [2, 3], [3, 1], [4, 3], [5, 3], [6, 2]] y_data = [[0], [0], [0], [1], [1], [1]] # placeholders for a tensor that will be always fed.

• deep-learning
• tensorflow
• regression
• logistic-regression
• classification

Logistic Regression 의 그래프 함수를 통과하기 전의 값을 Score(Logit) 이라 부른다. 통과한 난 뒤의 값은 확률이다.

• deep-learning
• tensorflow
• classification
• softmax
• cost-function
• cross-entropy

MNIST Dataset # Lab 7 Learning rate and Evaluation import tensorflow as tf import matplotlib.pyplot as plt import random tf.set_random_seed(777) # for reproducibility # 텐서플로우에서 데이터 받아오기 from tensorflow.examples.tutorials.mnist import input_data # Check out www.tensorflow.org/get_started/mnist/beginn...

• deep-learning
• tensorflow
• mnist
• classification