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Created 4 years ago
1. IMPORTING THE LIBRARIES
import numpy as np
import pandas as pd
from keras.models import Sequential
from keras.layers.core import Dense,Activation,Dropout
from keras.layers import LSTM
from sklearn.preprocessing import MinMaxScaler
from sklearn.metrics import mean_squared_error
import matplotlib.pyplot as plt
import time
import math
df = pd.read_csv('../input/IBM.csv',delimiter=',')
df=df.set_index(['date'])
df.drop(df.columns[[5,6,7,9]],axis=1,inplace=True)
df.head(5)
Using TensorFlow backend.
2.DATA VISUALISATION AND ANALYSIS
df.describe()
df.info()
<class 'pandas.core.frame.DataFrame'>
Index: 1258 entries, 2014-02-14 to 2019-02-13
Data columns (total 7 columns):
open 1258 non-null float64
high 1258 non-null float64
low 1258 non-null float64
close 1258 non-null float64
volume 1258 non-null int64
vwap 1258 non-null float64
changeOverTime 1258 non-null float64
dtypes: float64(6), int64(1)
memory usage: 78.6+ KB