Deep Learning ClassIntroductionSlidesWhat Is Deep Learning?SlidesBasic StatisticsSlidesDistributions and Sampling in PyTorchLectureExtendedA Basic Statistical Model in PyTorchLectureExtendedBasic Linear AlgebraSlidesTensorsSlidesTensors in PyTorchLectureExtendedGradientsSlidesFirst ExampleSlidesRegression and ClassificationSlidesDatasets and LossesSlidesLoss Functions in PyTorchLectureExtendedOptimizationSlidesComputational GraphsSlidesComputation Graphs in PyTorchLectureExtendedLinear Regression in PyTorchLectureExtendedBinary Logistic Regression in PyTorchLectureExtendedMulti-Class Logistic Regression in PyTorchLectureExtendedFirst Example - SummarySlidesDeep NetworksSlidesNonlinearitiesSlidesActivation FunctionsSlidesOutput RepresentationsSlidesLoss FunctionsSlidesStochastic Gradient DescentSlidesStochastic Gradient Descent in PyTorchLectureExtendedTraining a Deep Network in PyTorchLectureHyperparametersSlidesVariance Reduction in SGDSlidesDeep Networks in PyTorchLectureExtendedA Practical Guide to Deep Network DesignSlidesResiduals and NormalizationsSlidesVanishing and Exploding GradientsSlidesNormalizationsSlidesNormalizations in PyTorchLectureExtendedResidual ConnectionsSlidesResidual Connections in PyTorchLectureResiduals and Normalizations - SummarySlidesConvolutionSlidesConvolutionsSlidesStructure of ConvolutionsSlidesConvolutions in PyTorchLecturePoolingSlidesDesign Principles of Convolutional NetworksSlidesConvolutional Networks in PyTorchLectureDeep RepresentationsSlidesDilation and UpconvolutionSlidesDilation and Upconvolution in PyTorchLectureConvolution - SummarySlidesTransformersSlidesAttentionSlidesMulti-Head AttentionSlidesMulti-Head Attention in PyTorchLecturePositional EmbeddingsSlidesPositional Embeddings in PyTorchLectureThe Transformer ArchitectureSlidesThe Transformer Architecture in PyTorchLectureApplicationsSlidesTraining a Transformer in PyTorchinclass extendedTransformers - SummarySlidesMaking It WorkSlidesData and Advanced Network DesignSlidesAdvanced TrainingSlidesOverfittingSlidesMaking It Work in PyTorchinclassMaking It Work - SummarySlidesEnd of ClassSlides