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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...

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Building Transformer Models with Attention Crash Course. Build a Neural...

Last Updated on January 4, 2023 Transformer is a recent breakthrough in neural machine translation. Natural languages are complicated. A word in one language can be translated into multiple words in...

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Building a Softmax Classifier for Images in PyTorch

Last Updated on January 9, 2023 Softmax classifier is a type of classifier in supervised learning. It is an important building block in deep learning networks and the most popular choice among deep...

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Building a Single Layer Neural Network in PyTorch

Last Updated on January 10, 2023 A neural network is a set of neuron nodes that are interconnected with one another. The neurons are not just connected to their adjacent neurons but also to the ones...

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Neural Network with More Hidden Neurons

Last Updated on January 10, 2023 The traditional model of neural network is called multilayer perceptrons. They are usually made up of a series of interconnected layers. The input layer is where the...

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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...

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Manipulating Tensors in PyTorch

Last Updated on January 23, 2023 PyTorch is a deep learning library. Just like some other deep learning libraries, it applies operations on numerical arrays called **tensors**. In the simplest terms,...

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Using Autograd in PyTorch to Solve a Regression Problem

Last Updated on January 24, 2023 We usually use PyTorch to build a neural network. However, PyTorch can do more than this. Because PyTorch is also a tensor library with automatic differentiation...

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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...

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Develop Your First Neural Network with PyTorch, Step-by-Step

PyTorch is a powerful Python library for building deep learning models. It provides everything you need to define and train a neural network and use it for inference. You don’t need to write a lot of...

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Creating a Training Loop for PyTorch Models

PyTorch provides a lot of building blocks for a deep learning model, but training loop is not part of them. It is a flexibility provided that you can do whatever you want during training, but some...

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How to Evaluate the Performance of PyTorch Models

Designing a deep learning model is sometimes an art. There are a lot of decision points and it is not easy to tell what is the best. One way to come up with a design is by trial and error and...

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Building a Multiclass 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 tutorial, you will discover how to use PyTorch to develop and...

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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...

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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...

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Use PyTorch Deep Learning Models with scikit-learn

The most popular deep learning libraries in Python for research and development are TensorFlow/Keras and PyTorch, due to their simplicity. The scikit-learn library, however, is the most popular library...

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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...

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Save and Load Your PyTorch Models

A deep learning model is a mathematical abstraction of data, in which a lot of parameters are involved. Training these parameters can take hours, days, and even weeks but afterward, you can make use of...

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Using Activation Functions in Deep Learning Models

A deep learning model in its simplest form are layers of perceptrons connected in tandem. Without any activation functions, they are just matrix multiplications with limited power, regardless how many...

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Loss Functions in PyTorch Models

The loss metric is very important for neural networks. As all machine learning models are one optimization problem or another, the loss is the objective function to minimize. In neural networks, the...

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