Stock Price Prediction Using Python & Machine Learning

Using Python & Long Short-Term Memory (LSTM)

Disclaimer: The material in this article is purely educational and should not be taken as professional investment advice. Invest at your own discretion.

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In this article I will show you how to write a python program that predicts the price of stocks using a machine learning technique called Long Short-Term Memory (LSTM). This program is really simple and I doubt any major profit will be made from this program, but it’s slightly better than guessing! Remember the stock price can be affected by many different things.

Long short-term memory (LSTM) is an artificial recurrent neural network (RNN) architecture used in the field of deep learning. Unlike standard feed forward neural networks, LSTM has feedback connections. It can not only process single data points (such as images), but also entire sequences of data (such as speech or video). — Wikipedia

LSTMs are widely used for sequence prediction problems and have proven to be extremely effective.The reason they work so well is because LSTM is able to store past information that is important, and forget the information that is not. -Stackabuse.com

Common Architecture of LSTM:
Forget Gate
Input Gate
Output Gate

If you prefer not to read this article and would like a video representation of it, you can check out the YouTube Video below. It goes through everything in this article with a little more detail, and will help make it easy for you to start programming your own Machine Learning model even if you don’t have the programming language Python installed on your computer. Or you can use both as supplementary materials for learning about Machine Learning !