from flask import Flask 
#import seaborn as sns
#from sklearn.linear_model import LogisticRegression

app = Flask(__name__) 

@app.route('/') 
def hello_world(): 
     #iris1 =sns.load_dataset("iris")
     #modlog= LogisticRegression (max_iter=300)
     
    # irisarr = iris1.values
  #   X = irisarr[:,0:4]
    # Y = irisarr[:,4]
    
   #  modlog.fit(X,Y)
    
    # sl = 5.1
    # sw = 3.5 
    # pl = 1.4 
  #   pw = 0.2    #setosa
   #  res = modlog.predict([[ sl , sw ,pl ,pw ] ])
    
    return 'Hello, AIML july 25 batch' # + str(res[0])
  
if __name__ == "__main__":
    app.run(debug=True, host="0.0.0.0", port=5000)