Answer / Komal Prasad

The common steps for most TensorFlow algorithms can be summarized as follows: (1) Import necessary libraries, (2) Load or create datasets, (3) Define the model architecture using placeholders and operations, (4) Compile the computational graph, (5) Initialize variables, (6) Train the model by feeding data into the graph and updating weights, (7) Evaluate the performance of the model on validation sets, and (8) Optionally, test the model on new, unseen data.

What is deep speech?

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How can we create tensors from python objects?

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What is the difference between tensor.eval() and session.run()?

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Define sequence-to-sequence model?

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What do you understand by deep speech?

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What is tensorflow used for?

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Mention the name of some methods to deal with the overfitting in tensorflow.

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What is sequence-to-sequence model?

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What are tensorflow servables? Also, explain tensorflow serving.

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Can we implement classification in Tensorflow ? If Yes? What is function Name ?

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Explain few options to load data into tensorflow.

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