Categories: 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 the choice of activation functions. […]

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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…

March 6, 2023

In "AI/ML Research"

Building a Binary Classification Model in PyTorch

PyTorch library is for deep learning. Some applications of deep learning models are to solve regression or classification problems. In this post, you will discover how to use PyTorch to develop and evaluate neural network models for binary classification problems. After completing this post, you will know: How to load…

February 4, 2023

In "AI/ML Research"

Tips for Tuning Hyperparameters in Machine Learning Models

If you’re familiar with machine learning, you know that the training process allows the model to learn the optimal values for the parameters—or model coefficients—that characterize it. But machine learning models also have a set of hyperparameters whose values you should specify when training the model. So how do you…

August 7, 2024

In "AI/ML Research"

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