Australian (ASX) Stock Market Forum

Adventures in AI

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i have a membership with datacamp, doing there python courses. I haven't got to there AI/ML courses yet. But they do also offer python for finance stuff. So far, I'm a fan of them.

Are you going to use Norgate for your df/pandas of data? I see in their tutorial they use alphavantage.
 
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Yep, still using Norgate. I'm not really following their tutorial to a tee because I've already built a lot of the modules already that i'll just reuse, ie fetching data from Norgate, Index/Watchlist checking, pre processing the variables, scaling etc.

The biggest change so far is there's an extra dimension to the inputs.
- Simple NN input array shape ==== ( batch_size, number_of_features)
- LSTM input array shape ==== (batch_size, time_steps, number_of_features)

So i'm hoping to get out by 11 and enjoy the sunshine
 
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After the success of last week, this week has been a bit of a bust.

I am close to implementing an LSTM, it was a bit more work than i originally intended and still not done so i have no results to compare yet.

I am training it ok and It's definately a beast. I had to shrink the size of the network considerably to get it to train without running out of Memory and training time increased to 10 or so hours with a smallish network.

The evaluations that i can do are taking a minute to compute. The old network was in the mS so it's a few orders of magnitude in computational power to predict future prices. I don't know if it's going to be any better at it, i suspect it will revert to the mean like the other one did. I am hoping that it CAN pick out some patterns over time so i can compare the results between the 2 networks. Of all the types I've researched, LSTM is the one for this job.

I have also made the prediction time variable in both types of networks now. I am going to build individual networks to predict 1,2,3,5,8,13 etc days into the future and see if a shorter or longer time frame enhances it's abilities.

That's it for this week. Enjoy the sunshine
 
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