Not only am I forcing the Computer to do some machine learning but also I am making some ML approach
I have been learning about the Keras Sequential model and its layers and trying to make a better model by trying every possible combination. The problem here is that it takes several hours to process the whole dataset, which contains 3700 stock price charts from 2000-01-01 to 2019-12-31
And I got this model with 150 epochs.
250 epochs
Wait a minute, the data from around 2007 to 2009 might have much noise. Why do not we start in 2010? I will try it today and report tonight.
It seems there is a threshold of around 60%. Still targeting 75%
After 500 epochs with small batch sizes, it reached this.
After doing another 250 epochs, it, for some reason, reached its peak and did not change the val_acc anymore. It turned out the test accuracy was 61.3% after 750 epochs.
It might be possible that a better computer can result in better accuracy since a model with a better computational power can learn those pictures with a larger batch size without crashing.
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