Here, we are going to implement the neural network-based algorithm multilayer perceptron (MLP). You can refer to the following code snippet:

Figure 2.37: Code snippet for multilayer perceptron

Here, you can see that we are using the Relu activation function, and the gradient descent solver function is ADAM. We are using a learning rate of 0.0001. You can evaluate the result by referring to the following graph:

Figure 2.38: Code snippet for generating the graph for the actual and predicted prices

This graph shows that all the data records' predicted prices follow the actual price pattern. You can say that our MLP model works well to predict the stock market prices. You can find the code at this GitHub link: https://github.com/jalajthanaki/stock_price_prediction/blob/master/Stock_Price_Prediction.ipynb.