import pandas as pd
from sklearn import preprocessing
import numpy as np
import torch
import torch.optim as optim

# x_train = torch.FloatTensor([[1], [2], [3]])
# y_train = torch.FloatTensor([[2], [4], [6]])
#
# print(x_train)
# print(x_train.shape)
#
# w = torch.zeros(1, requires_grad=True)
# b = torch.zeros(1, requires_grad=True)
#
# h = x_train * w + b
# print(h)
# c = torch.mean((h - y_train)**2)
# print(c)
#
# o = optim.SGD([w, b], lr=0.01)
# o.zero_grad()
# c.backward()
# o.step()

# arr = np.array([[1,2,3], [4,5,6]])


## 데이터 준비
# data = {
#     'Hero':['Jack','Michael','Jim','Mengsk'],
#     'Age':[21,33,45,56]
# }
# df = pd.DataFrame(data)
# print(df)


