3 years ago

Category: Data, github, machine-learning

In this article, we will build a deep learning model (specifically the RNN Model) that will help us to predict whether the given stock will go up or down in the future. Remember, we are not interested in predicting the actual values as that will be far more complex compared to the prediction of the trend.

The dataset that we have used for this tutorial is of NSE Tata Global stock and is available on GitHub.

Now, we have initialized the MinMaxScalar that is used to scale every value in the range of 0 and 1.

After that, we have created NumPy arrays of both x_train and y_train for fast computation and reshaped the training set according to the requirement of our model.