Thicken Your Wallet with ML: Predict Stock Price Movements with LSTMs

This is a tutorial on how to use LSTMs for stock price movement prediction. I have seen quite a few tutorials on using LSTMs for stock price predictions and sadly most of them perform quite poorly. And the ones that actually work are sometimes poorly documented, so one can easily get lost in the wilderness of unforgiving-thorny-unexplained details.

The tutorial starts by looking at some basic averaging methods that can be used to model stock price movements. However these averaging methods rapidly become impotent when we need to predict multiple steps ahead with existing data.

On the other hand, LSTMs are much powerful in learning patterns in time-series data and highly regarded for their ability to persist long term memory sometimes for hundreds of time steps. Here we investigate how we can use LSTMs to decently predict stock price movements. This is what the results look like at the end of learning. Pretty impressive huh?

Full tutorial: Here

Note: If you enjoy the tutorial, make sure to upvote the post on DataCamp website. 🙂 I will be soon sharing the interactive Jupyter notebook as well.

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