wip host

.gitignore

@@ -15,3 +15,4 @@ models/trading_agent_final.pt.backup
 *.pt
 *.backup
 logs/
+trade_logs/

NN/_notes.md

@@ -2,13 +2,6 @@ great. realtime.py works. now let's examine and contunue with our  500m NN in a
 create a new main file in the NN folder for our new MoE model. we'll use one main NN module that will orchestrate data flows. our CNN module should have training and inference pipelines implemented internally, but the orchestrator will get the realtime data and forward it. use a common interface. another module later will be Transformer module that will take as input raw data from the latest hidden layers of the CNN where high end features are learned as well as the output, which will be BUY/HOLD/SELL signals as well as key support/resistance trend lines
 
 
-# setup:
-setup_env.bat
-
-# run:
-python -m NN.start_tensorboard --logdir=NN/models/saved/logs
-# and 
-run_nn.py / run_nn_in_conda.bat / run_pytorch_nn.bat
 
 # Train a CNN model
 python -m NN.main --mode train --symbol BTC/USDT --timeframes 1h 4h --model-type cnn --epochs 100