Convert code from cntk to keras

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Dear sridhardvvce Thank you for considering our services to convert your code from CNTK to Keras. Our bid for this task is [bid amount]. With our expertise in deep learning frameworks and extensive experience in both CNTK and Keras, we are well-equipped to handle this code conversion project. We will meticulously analyze your existing code, rewrite the necessary components in Keras syntax, and ensure seamless functionality and performance. We are committed to delivering a high-quality converted codebase that meets your requirements. Let's discuss further to initiate the code conversion process. Best regards, Kasia D.

"I'm skilled in Python and Keras, with a strong understanding of deep learning frameworks. I'll convert your CNTK code to Keras while ensuring accuracy. I'll also thoroughly test and optimize the code to guarantee its proper functionality. Let's make your Hangman game a machine learning success!"

Converting the code from CNTK to Keras may require changes and adjustments, but just maintaining a high level of accuracy may require adjustments and optimizations made in CNTK. Here is a general process for converting code from CNTK to Keras: Convert layers: We start converting layers from CNTK to Keras. The most optimal way to convert layers directly is to use existing equivalents of layers in Keras. For example, if the Convolutional layer in CNTK uses the Convolution function, its equivalent in Keras is the Conv2D function. Transform activation functions: Activation functions may be different in CNTK and Keras. We ensure that the activation functions used in CNTK are well ported to Keras. Converting optimizers and cost functions: Keras supports various optimizers and cost functions that may differ from those in CNTK. We need to port optimizers and cost functions from CNTK to Keras. Training the model: after converting the code to Keras, we train the model and compare the results. If the accuracy of the model does not reach the desired level, we may need more adjustments and optimizations in Keras. Finally, note that a full code conversion from CNTK to Keras can be time-consuming and difficult, requiring careful analysis of the code and documentation of both frameworks. Also, some features and settings available in CNTK may not exist in Keras and should be replaced using their equivalent functions and parameters in Keras.