Technical Interview Questions
When we first run the tf.Variable.initializer operation for a variable in a session, it is started. It is destroyed when we run the tf.Session.close operation. The lifetime of a variable refers to the duration during which the variable exists in the memory of a program. The specific lifetime of a variable depends on its scope … Read more
The intermediate tensors are tensors that are neither inputs nor outputs of the Session.run() call, but are in the path leading from the inputs to the outputs; they will be freed at or before the end of the call. Sessions can own resources, few classes like tf.Variable, tf.QueueBase, and tf.ReaderBase, and they use a significant … Read more
Gradient descent is an optimization algorithm that is used to find the coefficients of parameters that are used to reduce the cost function to a minimum. Step 1: Allocate weights (x,y) with random values and calculate the error (SSE) Step 2: Calculate the gradient, i.e., the variation in SSE when the weights (x,y) are changed … Read more
Components of GAN: Generator Discriminator Deployment Steps: Train the model Validate and finalize the model Save the model Load the saved model for the next prediction For an interview question regarding Generative Adversarial Networks (GANs), here’s a structured answer: Components of GAN: Generator: The generator network takes random noise as input and generates data samples … Read more
An autoencoder is basically used to learn a compressed form of the given data. A few applications of an autoencoder are given below: Data denoising Dimensionality reduction Image reconstruction Image colorization An autoencoder is a type of artificial neural network used for unsupervised learning. It aims to learn efficient data codings by training the network … Read more