arditobryan
/ Google Stock, LSTM prediction
Created
May 13, 2020 10:40
I will use a Vanilla LSTM to predict the GOOG Stock future performances
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| import sys | |
| sys.path.append('/content/drive/My Drive/Colab Notebooks/TensorFlow 2.0/modules') | |
| import pandas as pd | |
| import tf_dataset_extractor as e | |
| #import grapher_v1_1 as g | |
| #import LSTM_creator_v1_0 as l | |
| v = e.v | |
| g = e.g | |
| l = e.l |
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| #Generating the Data | |
| #convert boxplots to mean, sd, alpha | |
| def features_creator(boxplots): | |
| def boxplot_to_normal(Q1, Q2, Q3): | |
| sd = (Q3-Q1)*(3/4) | |
| mean = (Q1+(Q3-Q1)/2) #/(Q3-Q1) | |
| alpha = ((Q3-Q2)/(Q2-Q1)) #/(Q3-Q1) | |
| return mean, sd, alpha |