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author | bloodstalker <thabogre@gmail.com> | 2018-09-29 12:30:44 +0000 |
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committer | bloodstalker <thabogre@gmail.com> | 2018-09-29 12:30:44 +0000 |
commit | 3032bb77f3cb8a71fcd2ffeff5e1be63f5837ce8 (patch) | |
tree | 6feaa17b0feaf4f941720d85507d77add869288f /lstm.py | |
parent | update (diff) | |
download | seer-3032bb77f3cb8a71fcd2ffeff5e1be63f5837ce8.tar.gz seer-3032bb77f3cb8a71fcd2ffeff5e1be63f5837ce8.zip |
update
Diffstat (limited to 'lstm.py')
-rwxr-xr-x | lstm.py | 6 |
1 files changed, 4 insertions, 2 deletions
@@ -2,6 +2,8 @@ # _*_ coding=utf-8 _*_ #original source:https://github.com/dashee87/blogScripts/blob/master/Jupyter/2017-11-20-predicting-cryptocurrency-prices-with-deep-learning.ipynb +#@#!pip install lxml +#@#!mkdir lstm-models import argparse import code import readline @@ -134,10 +136,10 @@ def load_models(crypto, crypto_short): def premain(argparser): signal.signal(signal.SIGINT, SigHandler_SIGINT) #here - #lstm_type_1("ethereum", "ether") + lstm_type_1("ethereum", "ether") #lstm_type_2("ethereum", "ether", 5, 20) #lstm_type_3("ethereum", "ether", 5, 20) - load_models("ethereum", "eth") + #load_models("ethereum", "eth") def main(): argparser = Argparser() |