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Stock-Price-Prediction

Problem/ Project Description:

In this project we have a dataset containing stock prices of Google from January-2012 to December-2016. We are required to use these stock prices for training the neural network and predict the stock prices for the month of January-2017. This is a Regression problem.

Model used: Long Short-Term Memory (LSTM).

Tools Used: TensorFlow, Keras, Numpy, Pandas, Matplotlib

Language used: Python

Project: To see the project simply open the Jupyter Notebook, "Stock Price Prediction.ipynb"

BlogPost: Work in Progress

Try it Yourself: You can download and execute the python file after installing all the tools used.

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Prediction of stock prices using LSTM

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