How to use VarianceScaling initializer to a Deep Learning Model in Keras In deep learning, the initializer is a method used to set the initial values of the weights of the neural network. The initial values of the weights play a crucial role in the training process, as they determine how the network will …
How to use RandomNormal initializer in a Deep Learning Model in Keras In deep learning, the initializer is a method used to set the initial values of the weights of the neural network. The initial values of the weights play a crucial role in the training process, as they determine how the network will …
How to use l1_l2 regularization to a Deep Learning Model in Keras In deep learning, weight regularization is a technique used to prevent overfitting by adding a penalty term to the loss function. There are different types of weight regularization, but one of the most common is L1 regularization and L2 regularization. L1 regularization …
In deep learning, weight regularization is a technique used to prevent overfitting by adding a penalty term to the loss function. There are different types of weight regularization, but one of the most common is L2 regularization, also known as weight decay. L2 regularization adds a penalty term to the loss function that …
In deep learning, a dropout layer is a regularization technique that helps prevent overfitting by randomly dropping out (or turning off) a certain number of neurons during training. In other words, dropout layer randomly drops out a certain percentage of neurons in a layer, so that the neurons in the layer are not …
Deep learning is a type of machine learning that uses neural networks with multiple layers, called deep neural networks, to analyze and understand complex data, such as images, speech, and text. In this essay, we will be discussing how to set up a deep learning model using Keras, a popular open-source library for …
How to build simple Feed Forward Neural Network in Keras A feed forward neural network is a type of machine learning model that is used for tasks such as image recognition, speech recognition, and natural language processing. It is called a “feed forward” neural network because the data flows through the network in one …
How to setup a multiclass classification Deep Leaning Model in Keras? A multiclass classification deep learning model is a type of machine learning model that is used to classify items into multiple categories or classes. For example, it can be used to classify images of handwritten digits into the numbers 0-9. In this essay, …
How to setup a binary classification Deep Leaning Model in Keras A binary classification deep learning model is a type of model that is trained to classify data into two distinct classes. In Keras, setting up a binary classification deep learning model involves a few steps. First, you will need to import the …
How to split train and test datasets using validation_split in Keras? Splitting a dataset into a training and a test set is a crucial step when building a deep learning model. The training set is used to train the model and the test set is used to evaluate the model’s performance on unseen data. …