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for epoch in range(numEpochs):
train(...) #Training code
accuracy = eval(...) #Evaluate accuracy
#If we've reached a new best accuracy
if accuracy > best_accuracy:
#Save model checkpoint{'epoch': epoch,
'state_dict': model.state_dict(),
gagejustins /
Last active Apr 5, 2018
Code for Twitter algorithm spotlight
import Algorithmia
input = {
"username": "elonmusk",
"auth": {
"app_key": "xxxxxxxxxx",
"app_secret": "xxxxxxxxxx",
"oauth_token": "xxxxxxxxxx",
"oauth_token_secret": "xxxxxxxxxx"
gagejustins /
Last active Mar 23, 2018
Code for sentiment analysis with Twitter demo
#Define your API Key from Algorithmia
apikey = 'YOUR_API_KEY'
#Initialize the Algorithmia client
client = Algorithmia.client(apikey)
#Create an instance of the RetrieveTweetsWithKeyword algorithm
algo = client.algo('diego/RetrieveTweetsWithKeyword/0.1.2')
#Call the algorithm for both of our keywords and store the results
gagejustins /
Last active Mar 6, 2019
Code for my tutorial on CNNs in Pytorch
CNN = SimpleCNN()
trainNet(CNN, batch_size=32, n_epochs=5, learning_rate=0.001)
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