How to increase n_epoch level

[sarancruzer]

reset underlying graph data

tf.reset_default_graph()

Build neural network

net = tflearn.input_data(shape=[None, len(train_x[0])])
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, 8)
net = tflearn.fully_connected(net, len(train_y[0]), activation='softmax')
net = tflearn.regression(net)

Define model and setup tensorboard

model = tflearn.DNN(net, tensorboard_dir='tflearn_logs')

Start training (apply gradient descent algorithm)

model.fit(train_x, train_y, n_epoch=1000, batch_size=8, show_metric=True)
model.save('model.tflearn')

[MauryaRitesh]

Use n_epoch = 500000 or whatever, instead of 1000. Like this:
model.fit(train_x, train_y, n_epoch=500000, batch_size=8, show_metric=True)