{"id":129579,"date":"2023-05-09T17:21:10","date_gmt":"2023-05-09T11:51:10","guid":{"rendered":"https:\/\/www.vskills.in\/certification\/tutorial\/?page_id=129579"},"modified":"2024-04-12T14:23:56","modified_gmt":"2024-04-12T08:53:56","slug":"deep-learning-with-pytorch-glossary","status":"publish","type":"page","link":"https:\/\/www.vskills.in\/certification\/tutorial\/deep-learning-with-pytorch-glossary\/","title":{"rendered":"Deep Learning with PyTorch Glossary"},"content":{"rendered":"\n<p>Important definitions and terminologies used in Deep Learning with PyTorch<\/p>\n\n\n<div id=\"glossary\">\n<div id=\"letter-links\" style=\"font-size: 30px;letter-spacing:20px;\"><a href=\"#A\">A<\/a><a href=\"#B\">B<\/a><a href=\"#C\">C<\/a><a href=\"#D\">D<\/a><a href=\"#E\">E<\/a><a href=\"#F\">F<\/a><a href=\"#G\">G<\/a><a href=\"#H\">H<\/a><a href=\"#I\">I<\/a><a href=\"#J\">J<\/a><a href=\"#K\">K<\/a><a href=\"#L\">L<\/a><a href=\"#M\">M<\/a><a href=\"#N\">N<\/a><a href=\"#O\">O<\/a><a href=\"#P\">P<\/a><a href=\"#R\">R<\/a><a href=\"#S\">S<\/a><a href=\"#T\">T<\/a><a href=\"#U\">U<\/a><a href=\"#V\">V<\/a><a href=\"#W\">W<\/a><a href=\"#X\">X<\/a><a href=\"#Z\">Z<\/a><\/div>\n<h2 id=\"A\">A<\/h2>\n<ul>\n<li>Activation function in Deep Learning with PyTorch<\/li>\n<li>Adagrad in Deep Learning with PyTorch<\/li>\n<li>Adam in Deep Learning with PyTorch<\/li>\n<li>ATen in Deep Learning with PyTorch<\/li>\n<li>Attention mechanism in Deep Learning with PyTorch<\/li>\n<li>Autoencoder in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"B\">B<\/h2>\n<ul>\n<li>Backpropagation in Deep Learning with PyTorch<\/li>\n<li>Batch normalization in Deep Learning with PyTorch<\/li>\n<li>Batch size in Deep Learning with PyTorch<\/li>\n<li>Binary classification in Deep Learning with PyTorch<\/li>\n<li>Boltzmann machine in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"C\">C<\/h2>\n<ul>\n<li>Cascade training in Deep Learning with PyTorch<\/li>\n<li>CNN in Deep Learning with PyTorch<\/li>\n<li>Convolution in Deep Learning with PyTorch<\/li>\n<li>Convolution Operation in Deep Learning with PyTorch<\/li>\n<li>Convolutional autoencoder in Deep Learning with PyTorch<\/li>\n<li>Cross-entropy loss in Deep Learning with PyTorch<\/li>\n<li>Cross-validation in Deep Learning with PyTorch<\/li>\n<li>CUDA in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"D\">D<\/h2>\n<ul>\n<li>Data augmentation in Deep Learning with PyTorch<\/li>\n<li>Data loader in Deep Learning with PyTorch<\/li>\n<li>Data normalization in Deep Learning with PyTorch<\/li>\n<li>Deep belief network in Deep Learning with PyTorch<\/li>\n<li>Dimensionality reduction in Deep Learning with PyTorch<\/li>\n<li>Distributed Data-Parallel in Deep Learning with PyTorch<\/li>\n<li>Dropout in Deep Learning with PyTorch<\/li>\n<li>Dynamic Graphs in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"E\">E<\/h2>\n<ul>\n<li>Early fusion in Deep Learning with PyTorch<\/li>\n<li>Early stopping in Deep Learning with PyTorch<\/li>\n<li>Embedding in Deep Learning with PyTorch<\/li>\n<li>Ensemble learning in Deep Learning with PyTorch<\/li>\n<li>Epoch in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"F\">F<\/h2>\n<ul>\n<li>Feedforward neural network in Deep Learning with PyTorch<\/li>\n<li>Fine-tuned model in Deep Learning with PyTorch<\/li>\n<li>Fine-tuning in Deep Learning with PyTorch<\/li>\n<li>Focal loss in Deep Learning with PyTorch<\/li>\n<li>Fully connected layer in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"G\">G<\/h2>\n<ul>\n<li>GAN in Deep Learning with PyTorch<\/li>\n<li>Gated Recurrent Unit (GRU) in Deep Learning with PyTorch<\/li>\n<li>Generative model in Deep Learning with PyTorch<\/li>\n<li>Gradient descent in Deep Learning with PyTorch<\/li>\n<li>Gradient in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"H\">H<\/h2>\n<ul>\n<li>Hidden layer in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"I\">I<\/h2>\n<ul>\n<li>Inception in Deep Learning with PyTorch<\/li>\n<li>Inference in Deep Learning with PyTorch<\/li>\n<li>Input layer in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"J\">J<\/h2>\n<ul>\n<li>Jacobian matrix in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"K\">K<\/h2>\n<ul>\n<li>K-means clustering in Deep Learning with PyTorch<\/li>\n<li>Kernel in Deep Learning with PyTorch<\/li>\n<li>Kullback-Leibler divergence in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"L\">L<\/h2>\n<ul>\n<li>L1 regularization in Deep Learning with PyTorch<\/li>\n<li>L2 regularization in Deep Learning with PyTorch<\/li>\n<li>Label smoothing in Deep Learning with PyTorch<\/li>\n<li>LeakyReLU in Deep Learning with PyTorch<\/li>\n<li>Learning rate in Deep Learning with PyTorch<\/li>\n<li>Local response normalization in Deep Learning with PyTorch<\/li>\n<li>Loss function in Deep Learning with PyTorch<\/li>\n<li>LSTM in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"M\">M<\/h2>\n<ul>\n<li>Max pooling in Deep Learning with PyTorch<\/li>\n<li>Mean absolute error in Deep Learning with PyTorch<\/li>\n<li>Mean squared error in Deep Learning with PyTorch<\/li>\n<li>Memory network in Deep Learning with PyTorch<\/li>\n<li>Metric learning in Deep Learning with PyTorch<\/li>\n<li>Mini-batch gradient descent in Deep Learning with PyTorch<\/li>\n<li>Mini-batch in Deep Learning with PyTorch<\/li>\n<li>MobileNet in Deep Learning with PyTorch<\/li>\n<li>Momentum in Deep Learning with PyTorch<\/li>\n<li>Multi-class classification in Deep Learning with PyTorch<\/li>\n<li>Multi-layer perceptron in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"N\">N<\/h2>\n<ul>\n<li>Negative log-likelihood loss in Deep Learning with PyTorch<\/li>\n<li>Nesterov momentum in Deep Learning with PyTorch<\/li>\n<li>Non-maximum suppression in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"O\">O<\/h2>\n<ul>\n<li>Object detection in Deep Learning with PyTorch<\/li>\n<li>One-hot encoding in Deep Learning with PyTorch<\/li>\n<li>Optimizer in Deep Learning with PyTorch<\/li>\n<li>Overfitting in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"P\">P<\/h2>\n<ul>\n<li>Padding in Deep Learning with PyTorch<\/li>\n<li>Perceptron in Deep Learning with PyTorch<\/li>\n<li>Pre-trained model in Deep Learning with PyTorch<\/li>\n<li>Probabilistic graphical model in Deep Learning with PyTorch<\/li>\n<li>PyTorch in Deep Learning with PyTorch<\/li>\n<li>PyTorch Lightning in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"R\">R<\/h2>\n<ul>\n<li>Radial basis function network in Deep Learning with PyTorch<\/li>\n<li>Random forest in Deep Learning with PyTorch<\/li>\n<li>Ranking loss in Deep Learning with PyTorch<\/li>\n<li>Recurrent neural network (RNN) in Deep Learning with PyTorch<\/li>\n<li>Regularization in Deep Learning with PyTorch<\/li>\n<li>ReLU in Deep Learning with PyTorch<\/li>\n<li>Residual connections in Deep Learning with PyTorch<\/li>\n<li>ResNet in Deep Learning with PyTorch<\/li>\n<li>RNN in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"S\">S<\/h2>\n<ul>\n<li>Scheduling learning rate in Deep Learning with PyTorch<\/li>\n<li>Sequence to sequence (seq2seq) model in Deep Learning with PyTorch<\/li>\n<li>Sigmoid activation function in Deep Learning with PyTorch<\/li>\n<li>Sigmoid in Deep Learning with PyTorch<\/li>\n<li>Softmax in Deep Learning with PyTorch<\/li>\n<li>Stochastic gradient descent in Deep Learning with PyTorch<\/li>\n<li>Stochastic weight averaging (SWA) in Deep Learning with PyTorch<\/li>\n<li>Stride in Deep Learning with PyTorch<\/li>\n<li>Support vector machine (SVM) in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"T\">T<\/h2>\n<ul>\n<li>Tensor in Deep Learning with PyTorch<\/li>\n<li>TorchScript in Deep Learning with PyTorch<\/li>\n<li>Transfer learning in Deep Learning with PyTorch<\/li>\n<li>Transformer in Deep Learning with PyTorch<\/li>\n<li>Triplet loss in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"U\">U<\/h2>\n<ul>\n<li>U-Net in Deep Learning with PyTorch<\/li>\n<li>Unsupervised learning in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"V\">V<\/h2>\n<ul>\n<li>Validation set in Deep Learning with PyTorch<\/li>\n<li>Vanishing gradient problem in Deep Learning with PyTorch<\/li>\n<li>Variational autoencoder in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"W\">W<\/h2>\n<ul>\n<li>Weight decay in Deep Learning with PyTorch<\/li>\n<li>Weight initialization in Deep Learning with PyTorch<\/li>\n<li>Word2Vec in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"X\">X<\/h2>\n<ul>\n<li>Xavier initialization in Deep Learning with PyTorch<\/li>\n<li>Xavier normal initialization in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<h2 id=\"Z\">Z<\/h2>\n<ul>\n<li>Zero-padding in Deep Learning with PyTorch<\/li>\n<li>Zoneout in Deep Learning with PyTorch<\/li>\n<\/ul>\n<div><a href=\"#top\">Go to Top<\/a><\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Important definitions and terminologies used in Deep Learning with PyTorch ABCDEFGHIJKLMNOPRSTUVWXZ A Activation function in Deep Learning with PyTorch Adagrad in Deep Learning with PyTorch Adam in Deep Learning with PyTorch ATen in Deep Learning with PyTorch Attention mechanism in Deep Learning with PyTorch Autoencoder in Deep Learning with PyTorch Go to Top B Backpropagation&#8230;<\/p>\n","protected":false},"author":10,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"categories":[],"tags":[],"class_list":["post-129579","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.5 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Deep Learning with PyTorch Glossary - Tutorial<\/title>\n<meta name=\"description\" content=\"What is Deep Learning with PyTorch? 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