Justin Gage gagejustins

## jordan_prices.csv

          
            date
            value

            
              11/1/15
              300

            
              12/1/15
              378.375

            
              1/1/16
              333.7916667

            
              2/1/16
              330.7696078

            
              3/1/16
              347.2945545

            
              4/1/16
              363.2814465

            
              5/1/16
              323.4774096

            
              6/1/16
              288.9470878

            
              7/1/16
              284.7981057

## call.py
CNN = SimpleCNN()
trainNet(CNN, batch_size=32, n_epochs=5, learning_rate=0.001)

## optimizer.py
#Import the optim module from the pytorch package
import torch.optim as optim

#Initialize an optimizer object
learning_rate = 0.001
optimizer = optim.Adam(net.parameters(), lr=learning_rate)

#Set the parameter gradients to 0 and take a step (as part of a training loop)
for epoch in num_epochs:
train(...)
	date	value
	11/1/15	300
	12/1/15	378.375
	1/1/16	333.7916667
	2/1/16	330.7696078
	3/1/16	347.2945545
	4/1/16	363.2814465
	5/1/16	323.4774096
	6/1/16	288.9470878
	7/1/16	284.7981057
	CNN = SimpleCNN()
	trainNet(CNN, batch_size=32, n_epochs=5, learning_rate=0.001)
	#Import the optim module from the pytorch package
	import torch.optim as optim

	#Initialize an optimizer object
	learning_rate = 0.001
	optimizer = optim.Adam(net.parameters(), lr=learning_rate)

	#Set the parameter gradients to 0 and take a step (as part of a training loop)
	for epoch in num_epochs:
	train(...)