Creating Bitcoin trading bot that could beat the market #3

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In this tutorial, we will continue developing a Bitcoin trading bot, but this time instead of doing trades randomly, we'll use the power of reinforcement learning.

The purpose of the previous and this tutorial is to experiment with state-of-the-art deep reinforcement learning technologies to see if we can create a profitable Bitcoin trading bot. There are many articles on the internet, that states, that neural networks can't beat the market. However, recent advances in the field have shown that RL agents are often capable of learning much more than supervised learning agents within the same problem domain. For this reason, I am writing these tutorials to experiment if it's possible, and if it is, how profitable we can make these trading bots.

While I won't be creating anything quite as impressive as OpenAI engineers do, it is still not an easy task to trade Bitcoin profitably on a day-to-day basis and do it in a profit!

Text version tutorial: RL-BTC-BOT-NN/
GitHub code: pythonlessons/RL-Bitcoin-trading-bot/tree/main/RL-Bitcoin-trading-bot_3

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