add one model with tensorflow as sample

README.md

@@ -13,7 +13,6 @@ thumbnail: "url to a thumbnail used in social sharing"
 tags:
 - speech
 - audio
-- flair
 license: "any valid license identifier"
 datasets:
 - dataset1

kilomileprediction.py

@@ -0,0 +1,94 @@
+#!/usr/bin/env python
+# coding: utf-8
+
+# In[ ]:
+
+
+import tensorflow as tf
+import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
+import os
+
+# print(os.getcwd())
+
+#df = pd.read_csv('/mnt/batch/tasks/shared/LS_root/mounts/clusters/computeforaml/code/Users/luolala701/Kilometres-miles.csv')
+# df.info
+df = pd.read_csv('C://Users//luona//Downloads//Kilometres-miles.csv')
+
+
+# In[10]:
+
+
+#print('Painting the correlations')
+#sns.scatterplot(df['Kilometres'], df['Miles'])
+#plt.show()
+
+
+# In[13]:
+
+
+print('Define input(X) and output(Y) variables')
+X_train = df['Kilometres']
+Y_train = df['Miles']
+
+
+# In[16]:
+
+
+print('Creating the model')
+model = tf.keras.Sequential()
+model.add(tf.keras.layers.Dense(units=1, input_shape=[1]))
+
+
+# In[17]:
+
+
+print('Compiling the model')
+model.compile(optimizer=tf.keras.optimizers.Adam(1), loss='mean_squared_error')
+
+
+# In[18]:
+
+
+print('Training the model')
+epochs_hist = model.fit(X_train, Y_train, epochs = 250)
+
+
+# In[19]:
+
+
+print('Evaluating the model')
+print(epochs_hist.history.keys())
+
+#graph
+plt.plot(epochs_hist.history['loss'])
+plt.title('Evolution of the error associated with the model')
+plt.xlabel('Epoch')
+plt.ylabel('Training Loss')
+plt.legend('Training Loss')
+plt.show()
+
+
+# In[20]:
+
+
+kilometers = 100
+predictedMiles = model.predict([kilometers])
+print("The conversion from Kilometres to Miles is as follows: " + str(predictedMiles))
+
+
+# In[21]:
+
+
+milesByFormula = kilometers * 0.6214
+print("The conversion from kilometers to miles using the mathematical formula is as follows:" + str(milesByFormula))
+diference = milesByFormula - predictedMiles
+print("Prediction error:" + str(diference))
+
+
+# In[ ]:
+
+
+
+

requirements.txt

@@ -0,0 +1,4 @@
+tensorflow 
+pandas
+seaborn 
+matplotlib