Categories: AI/ML Research

Training Logistic Regression with Cross-Entropy Loss in PyTorch

Last Updated on March 28, 2023 In the previous session of our PyTorch series, we demonstrated how badly initialized weights can impact the accuracy of a classification model when mean square error (MSE) loss is used. We noticed that the model didn’t converge during training and its accuracy was also significantly reduced. In the following, […]

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Building a Logistic Regression Classifier in PyTorch

Logistic regression is a type of regression that predicts the probability of an event. It is used for classification problems and has many applications in the fields of machine learning, artificial intelligence, and data mining. The formula of logistic regression is to apply a sigmoid function to the output of…

March 29, 2023

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Introduction to Softmax Classifier in PyTorch

Last Updated on January 1, 2023 While a logistic regression classifier is used for binary class classification, softmax classifier is a supervised learning algorithm which is mostly used when multiple classes are involved. Softmax classifier works by assigning a probability distribution to each class. The probability distribution of the class…

January 16, 2023

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Building a Regression 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 regression problems. After completing this post, you will know: How to load data…

February 6, 2023

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