Upload New File- DMT 1 -testing train data

Untitled.py

+#!/usr/bin/env python
+# coding: utf-8
+
+# In[13]:
+
+
+import tensorflow as tf
+
+mnist = tf.keras.datasets.mnist
+
+(x_train, y_train), (x_test, y_test) = mnist.load_data()
+
+x_train = tf.keras.utils.normalize(x_train, axis=1)
+x_test = tf.keras.utils.normalize(x_test, axis=1)
+
+model = tf.keras.models.Sequential()
+model.add(tf.keras.layers.Flatten())
+model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
+model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
+model.add(tf.keras.layers.Dense(10, activation=tf.nn.softmax))
+model.compile(optimizer='adam',loss='sparse_categorical_crossentropy',
+                metrics=['accuracy'])
+model.fit(x_train, y_train, epochs=3)
+
+
+# In[14]:
+
+
+val_loss, val_acc = model.evaluate(x_test, y_test)
+print(val_loss,val_acc)
+
+
+# 
+
+# In[11]:
+
+
+import matplotlib.pyplot as plt
+
+
+plt.imshow(x_train[0], cmap = plt.cm.binary)
+plt.show()
+print(x_train[0])
+
+
+# In[36]:
+
+
+model.save("num_reader.model")
+
+
+# In[38]:
+
+
+predictions = new_model.predict([x_test])
+print(predictions)
+
+
+# In[33]:
+
+
+predictions =  new_model.predict([x_test])
+
+
+# In[20]:
+
+
+print(predictions)
+
+
+# In[ ]:
+
+
+import numpy as np
+
+print(np.argmax)
+