In this video will show you how to write a Python program that predicts the price of stocks using two different Machine Learning Algorithms, one is called a Support Vector Regression (SVR) and the other is Linear Regression. So you can start trading and making money ! Actually this program is really simple and I doubt any major profit will be made from this program, but it’s slightly better than guessing!

NOTE: Some errors in the video:

(1) In the video to calculate the RMSE I put the following statement:

rmse=np.sqrt(np.mean((predictions- y_test)**2))

When in fact I meant to put:

rmse=np.sqrt(np.mean(((predictions- y_test)**2)))

You can also use the following statements to calculate RMSE:

1. rmse =np.sqrt(np.mean(((predictions- y_test)**2)))

2. rmse = np.sqrt(np.mean(np.power((np.array(y_test)-np.array(predictions)),2)))

3. rmse = np.sqrt(((predictions - y_test) ** 2).mean())

(2) The preprocessing of data using MinMaxScaler resulted in data leakage, leading to the creation of future bias. Despite this, the code can still be utilized to obtain a basic understanding of Neural Network implementation in Python for classification and prediction purposes.

**Get the code here:**

https://github.com/randerson112358/Python/blob/master/LSTM_Stock/LSTM2.ipynb

#python #machine-learning #data-science #developer #artificial-intelligence

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