TensorFlow “fit” method is used to fit a model to training data. The fit method trains a model on
the training data by updating the model parameters so that the model predictions are as close as
possible to the true target values in the training data. This process is called model fitting or
model training. The fit method adjusts the model parameters to minimize a ...
Grid Search can be seen as an exhaustive search for the optimal set of hyperparameters. It is
computationally expensive and is usually used when the number of hyperparameters is relatively
small. To overcome the computational cost ...
Batch Normalization is a widely used technique in deep learning to improve the training stability
and performance of neural networks. It works by normalizing the activations of each layer in the
network, which helps to reduce the internal covariate shift and the chances of overfitting.
Advantages of using Batch Normalization...
A scheduled learning rate refers to a strategy for dynamically changing the learning rate during the
training process. The schedule is set in advance and is used to control the magnitude of...
how to implement a GAN using TensorFlow and generate fake tabular data from real data;
1-Define the generator model: The generator model is a neural network that takes a random...
