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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