State of Neural Networks strategies
It appears to me that the development of Neural Network based strategies for Gekko have gone a bit... stale?

The best article so far on this topic has been written by Deandree Blake at (see: "Crypto Trading 2018 in Review: 17 Advanced + 15 Neural Net strategies tested", also referred to on this forum "Neural Network strategy backtest comparison": ) So far the most helpful resources I have seen, yet this all is about 2018.

Deandree but also others on various postings seem to grab their strategies from the infamous xFFFFF Gekko-Strategies Github repository: Latest commit was on 24 May 2018. Not very active....

As Deandree points out in his article: "All strategies share some common traits: they use some kind of NN lib. Most (13/15) use convnetjs. The other 2 use LSTM type lib — synaptic or neataptic."

So 13/15 of the Neural Net strategies in the xFFFFF repository are using convnetjs ( Latest commit on 24 Nov 2016. The most popular neural network library has not been maintained in 3 years... Dodgy
1/15 strat (gekkoNeatapticIndicator) uses Neataptic: Last commit on 9 Jun 2018 over a year without maintenance

1/15 strat (LSTM_MACD_RSI_V3) uses Synaptic: Last commit 14 Feb (2019 that is, I assume, reasonably active)

So here we have it: Only LSTM_MACD_RSI_V3 uses a neural network library that is up to date (and gets points for clean code) but sadly, LSTM_MACD_RSI_V3 does not score very well in Deandree's backtesting...

Is this really the best we have? Does anyone know of more up to date information? 

NOTE: It looks like zuki_nn is so far one of the best neural networks out there and it relies on a 2016 neural network library... so yes I do newer does not necessarily mean better. However, it seems things have gone stale since the 2018 crypto bear market. I am just curious to see if anything significant has happened since.
Increment shrouded Layers. ...

Change Activation work. ...

Change Activation work in Output layer. ...

Increment number of neurons. ...

Weight introduction. ...

More information. ...

Normalizing/Scaling information.
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