Tag Archives: tensorflow

How to use RandomizedSearchCV in Deep Leaning using Keras

How to use RandomizedSearchCV in Deep Leaning using Keras   Randomized search is a technique used to find the best set of hyperparameters for a machine learning model. It is similar to grid search but instead of trying out all possible combinations of hyperparameters, it randomly samples a given number of combinations. It can be …

How to use GridSerachCV in Deep Leaning using Keras

How to use GridSerachCV in Deep Leaning using Keras   Grid search is a technique used to find the best set of hyperparameters for a machine learning model. It involves specifying a range of possible values for each hyperparameter and training the model for each combination of hyperparameter values. The goal is to find the …

How to setup a regression Deep Leaning Model in Keras

How to setup a regression Deep Leaning Model in Keras   Regression is a type of supervised machine learning problem where the goal is to predict a continuous value, such as the price of a stock, the temperature, or the weight of an object. In deep learning, a regression model is a neural network that …

How to setup a multiclass classification Deep Leaning Model in Keras

How to setup a multiclass classification Deep Leaning Model in Keras   Multiclass classification is a type of supervised machine learning problem where the goal is to predict one of multiple possible outcomes. For example, classifying images of animals into different categories such as cats, dogs, lions and so on. In deep learning, a multiclass …

How to setup a binary classification Deep Leaning Model in Keras

How to setup a binary classification Deep Leaning Model in Keras     Binary classification is a type of supervised machine learning problem where the goal is to predict one of two possible outcomes, such as “yes” or “no”, “true” or “false”, or “0” or “1”. In deep learning, a binary classification model is a …

How to split train and test datasets using validation_split in Keras

How to split train and test datasets using validation_split in Keras   When training a deep learning model, it’s important to evaluate its performance on unseen data, to make sure it generalizes well to new examples. To do this, you need to split your data into a training set, which is used to train the …

How to split train and test datasets in a Deep Leaning Model in Keras

How to split train and test datasets in a Deep Leaning Model in Keras   When training a deep learning model, it’s important to evaluate its performance on unseen data, to make sure it generalizes well to new examples. To do this, you need to split your data into a training set, which is used …

How to setup Early Stopping in a Deep Learning Model in Keras

How to setup Early Stopping in a Deep Learning Model in Keras   Early stopping is a technique used to stop training a deep learning model when the performance of the model on a validation dataset stops improving. The idea behind early stopping is to prevent overfitting by stopping the training process before the model …

How to create FeedForward Neural Networks in Keras

How to create FeedForward Neural Networks in Keras     A feedforward neural network, also known as a multi-layer perceptron (MLP), is a type of neural network that consists of an input layer, one or more hidden layers, and an output layer. Each layer is made up of a set of neurons, which are connected …

How to use VarianceScaling initializer to a Deep Learning Model in Keras

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 …