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--- a/README.md
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-# Tensorflow Quantum + K8s
+# PoC: K8s Quantum Tensorflow Machine Learning deployment in K8s
 
+<br>
 
 ## Theoretical Introduction
 
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 --- 
 
+<br>
+
 ## Steps:
 
 ### Prepare a quantum dataset
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 - After evaluating the cost function, the free parameters in the pipeline should be updated in a direction expected to decrease the cost.
 - This is most commonly performed via gradient descent.
 
-
+<br>
 
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 * [TensorFlow Quantum](https://github.com/tensorflow/quantum/blob/master/docs/install.md).
 
 
+<br>
+
 ----
 
 ### References