Categories: AI/ML Research

Building a Convolutional Neural Network in PyTorch

Neural networks are built with layers connected to each other. There are many different kind of layers. For image related applications, you can always find convolutional layers. It is a layer with very few parameters but applied over a large sized input. It is powerful because it can preserve the spatial structure of the image. […]

The post Building a Convolutional Neural Network in PyTorch appeared first on MachineLearningMastery.com.

Building an Image Classifier with a Single-Layer Neural Network in PyTorch

Last Updated on January 18, 2023 A single-layer neural network, also known as a single-layer perceptron, is the simplest type of neural network. It consists of only one layer of neurons, which are connected to the input layer and the output layer. In case of an image classifier, the input…

January 18, 2023

In "AI/ML Research"

Building Multilayer Perceptron Models in PyTorch

Last Updated on January 27, 2023 The PyTorch library is for deep learning. Deep learning, indeed, is just another name for a large scale neural network or multilayer perceptron network. In its simplest form, multilayer perceptrons are a sequence of layers connected in tandem. In this post, you will discover…

January 27, 2023

In "AI/ML Research"

How to Grid Search Hyperparameters for PyTorch Models

The “weights” of a neural network is referred as “parameters” in PyTorch code and it is fine-tuned by optimizer during training. On the contrary, hyperparameters are the parameters of a neural network that is fixed by design and not tuned by training. Examples are the number of hidden layers and…

February 10, 2023

In "AI/ML Research"

AI Generated Robotic Content