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p2_1.py

+
+# coding: utf-8
+
+# In[2]:
+
+
+from keras.models import Sequential
+from keras.layers import Dense
+import numpy as np
+import pandas as pd
+
+
+# In[15]:
+
+
+data=np.loadtxt("and.csv",delimiter=",")
+
+
+# In[31]:
+
+
+x=data[:,0:2]
+
+
+# In[32]:
+
+
+y=data[:,2]
+
+
+# In[38]:
+
+
+model=Sequential()
+model.add(Dense(8,input_dim=2,activation='relu'))
+model.add(Dense(6,activation='relu'))
+model.add(Dense(1,activation='sigmoid'))
+
+
+# In[39]:
+
+
+model.compile(loss='binary_crossentropy',optimizer='adam',metrics=['accuracy'])
+history=model.fit(x,y,epochs=100,batch_size=2)
+
+
+# In[40]:
+
+
+l,a=model.evaluate(x,y)
+
+
+# In[41]:
+
+
+print(l,a)
+
+
+# In[50]:
+
+
+c=np.array([[1,1],[0,1],[1,0],[0,0]])
+q=model.predict(c)
+a=[]
+for i in q:
+    print(i)
+