Month: March 2020

How to classify Flowers (iris data) using a keras deep learning model

How to classify Flowers (iris data) using a keras deep learning model     Classifying flowers, specifically the iris data, using a keras deep learning model is a process that involves several steps. The Iris dataset is a popular dataset for classification tasks, and it consists of 150 samples of iris flowers, each with four …

How to classify images using CIFAR10 dataset in Keras

How to classify images using CIFAR10 dataset in Keras     Classifying images using the CIFAR-10 dataset in Keras involves several steps. First, you need to import the CIFAR-10 dataset, which is a dataset of 60,000 color images of 32×32 pixels, divided into 10 classes. Each image belongs to one of the following classes: airplanes, …

How to setup a Regression Experiment using Boston Housing dataset in Keras

How to setup a Regression Experiment using Boston Housing dataset in Keras     Setting up a regression experiment using the Boston Housing dataset in Keras involves several steps. First, you need to import the Boston Housing dataset, which contains information about the median value of homes in the Boston area, and various features of …

How to setup a Binary Classification Experiment using IMDB dataset in Keras

How to setup a Binary Classification Experiment using IMDB dataset in Keras   Setting up a binary classification experiment using the IMDB dataset in Keras involves several steps. First, you need to import the IMDB dataset, which is a dataset of movie reviews and their corresponding labels (positive or negative). The dataset contains 25,000 reviews …

How to setup a Multiclass Classification Experiment using Fashion MNIST dataset in Keras

How to setup a Multiclass Classification Experiment using Fashion MNIST dataset in Keras     Setting up a multiclass classification experiment using the Fashion MNIST dataset in Keras involves several steps. First, you need to import the Fashion MNIST dataset, which is a dataset of images of clothing items and their corresponding labels. The dataset …

How to setup an experiment in a Deep Learning model

How to setup an experiment in a Deep Learning model     Setting up an experiment in a deep learning model is the process of designing a controlled study to evaluate the performance of a model on a specific task or problem. The goal of an experiment is to test the performance of the model …

How to test different OPTIMIZERs and Epoch Sizes in a Deep Learning model

How to test different OPTIMIZERs and Epoch Sizes in a Deep Learning model     Testing different optimizers and epoch sizes in a deep learning model is a way to evaluate which combination of optimizer and number of training iterations (epochs) works best for a specific problem. Optimizers are used to adjust the weights of …

How to test different OPTIMIZERs in a Deep Learning model

How to test different OPTIMIZERs in a Deep Learning model   Testing different optimizers in a deep learning model is a way to evaluate which optimizer works best for a specific problem. Optimizers are used to adjust the weights of the model to minimize the loss function, and different optimizers can have different properties that …

How to test RMSprop() OPTIMIZER in a Deep Learning model

How to test RMSprop() OPTIMIZER in a Deep Learning model     RMSprop is an optimizer used in deep learning to update the weights of a model during training. Optimizers are used to adjust the weights of the model to minimize the loss function, and different optimizers can have different properties that make them more …

How to reduce overfitting in a Deep Learning model

How to reduce overfitting in a Deep Learning model   Overfitting is a common problem in deep learning, where a model becomes too complex and starts to memorize the training data instead of generalizing to new unseen data. This can lead to poor performance on new data and a high training accuracy but a low …