Inventory Worth Prediction Utilizing Python & Machine Studying (LSTM).
On this video you’ll discover ways to create a man-made neural community known as Lengthy Quick Time period Reminiscence to foretell the long run worth of inventory.
Disclaimer: The fabric on this video is solely instructional and shouldn’t be taken as skilled funding recommendation. Make investments at your individual discretion.
NOTE: Within the video to calculate the RMSE I put the next assertion:
rmse=np.sqrt(np.imply((predictions- y_test)**2))
When in truth I meant to place :
rmse=np.sqrt(np.imply(((predictions- y_test)**2)))
You should utilize the next statements to calculate RMSE:
1. rmse =np.sqrt(np.imply(((predictions- y_test)**2)))
2. rmse = np.sqrt(np.imply(np.energy((np.array(y_test)-np.array(predictions)),2)))
3. rmse = np.sqrt(((predictions – y_test) ** 2).imply())
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