if you are loading your data to a numpy array, do as follow:
dataset = torch.from_numpy(data)

and if your data is loading to python list:
dataset = torch.tensor(data)

for data normalization:
dMin  = (dataset.min(0,keepdim=True))[0]
dMax = (dataset.max(0,keepdim=True))[0]
NDataset = (dataset - dMin)/(dMax - dMin)

then you need to define data loader:
dl = torch.utils.data.DataLoader(NDataset,batch_size=100,shuffle=True)

for i in range(epoch):
    for x in dl:
         #do something with it.