TensorFlow building and training a simple model: Exercises and solutions

Python TensorFlow building and training a simple model [9 exercises with solution]

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Creating a Computational Graph:

1. Write a Python program that creates a TensorFlow placeholder for input data of shape (None, 20) where "None" represents a variable batch size.
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2. Write a Python program that defines a TensorFlow constant tensor containing weights for a neural network layer with shape (10, 4).
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3. Write a Python program that creates a TensorFlow operation to perform matrix multiplication between two tensors.
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4. Write a Python program that builds a feedforward neural network using TensorFlow with one hidden layer and a sigmoid activation function.
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5. Write a Python program that creates a TensorFlow placeholder for a 3D tensor representing images with dimensions (batch_size, height, width).
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Defining a Loss Function:

6. Write a Python program that defines a mean squared error (MSE) loss function using TensorFlow for a regression task.
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7. Write a Python program that implements a categorical cross-entropy loss function using TensorFlow for a multi-class classification problem.
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8. Write a Python program that creates a custom loss function using TensorFlow that penalizes errors differently for positive and negative examples.
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9. Write a Python program that creates a custom loss function in TensorFlow that penalizes errors differently for positive and negative examples.
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Gradient Descent Optimization:

10. Write a Python program that implements a gradient descent optimizer using TensorFlow for a simple linear regression model.
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11. Write a Python program that implements a gradient descent optimizer using TensorFlow for a simple linear regression model.
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12. Write a Python program to experiment with different learning rates in a gradient descent optimizer and observe the impact on convergence in TensorFlow.
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