How to Code a Bitcoin Bot in Python – Machine Learning Tutorial
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In this video, you will learn how to create a cryptocurrency trading algorithm that uses machine learning to make trading decisions. We will develop a neural network to predict Bitcoin’s price direction. Besides Bitcoin, you could also use this tutorial for other cryptos, stocks, forex, or whatever else you want to trade.
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Vídeo
thanks for great video. I have a question. 9:59 should the optimal value be 50?
Dude lol you need to get a quieter keyboard this is like ASMR STUFF lol and I can’t stand that sound lol
How would you link this to a coinbase api?
Could you pls also briefly explain how to interprete the backtest report; the sharpe ratio and co. Thank you
Thank you for the knowledge. Please i have the following questions.
1). I would like to add some indicators (e.g ATR, RSI, MACD etc) to my dataframe to be used an input into the neural network mode. Do you advice these are added before taking the % change of the OHLC values or after? Do I also need to apply the pct_change () on these indicator values or just on the prices?
2). Assuming i have an already trained and saved model, how can it be imported into Quant connect to be used for building the bot?
3). Do you advise a data normalization, especially after taking the % change of the OHLC and adding indicators?
Very cool, but I thought you were going to let it run the sample data over and over again until it was performing well and predicting the market with a higher win rate percentage each time, isn't that the whole point of machine learning?
Another great video. Real gems for aspiring algo traders. please continue. Thank you for your work
Thanks! Very interesting! Get a question though, why the backtest result of same timeframe could be significantly different every time? even I haven't change anything on the model itself after it was once saved as object to the ObjectStore? I mean most backtest run was -ve return but vary from -85% to -50% and one was +ve return. Am I missing something?
Are your trained weights also being saved to the ObjectStore?
Just a quick question, do you need money to make this?
Is there a tutorial that explains this a simpler way?
By following your guide, I'm able to get the code work successfully. However, when I changed resolution from Daily to Hour, I finished running model, but when backtesting, the test ran for a short time, until it stopped due to the Error: Error when checking input: expected dense_input to have shape (30, 5) but got array with shape (29, 5) at standardize_input_data. I expect there was something wrong with the data got from coinbase. How can I fix this problem?
what's your accuracy percentage? what currency did you test this under ?
Hi does the program not require block chain ?
Also like your work. Thanks for sharing .
Grazie.
Great tutotrial! thank you so much for your effort. Are you evaluating the possibility for a video about Reinforcement learning algorithm?
Hello TradeOptionsWithMe!
Awesome video, one question; in 12:56 the neuralnetwork will overfit itself if you have too many epochs. Why is that? Since you want the model to adjust itself to the data so it's better prepared for unknown data right? So I don't really understand why you would only want it to run 5 times and not say 20.
would be cool if u could show how to use keras tuner to improve the network structure
I love this video, could you make more machine learning video’s in the future? Thank you!
Thanks a lot ! Your channel is awesome, thanks for sharing !
Building a profitable trading bot is harder than you think. It is not enough just to be a good software engineer you also have to be a good trader with many years of experience.
👍🏽
Getting an error stating object has no attribute while backtesting the clone, please assist