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01:12:20 Advanced Machine Learning 2022 - day 28 Style… Advanced Machine Learning 2022 - day 28 Style Transfer	Advanced Machine Learning 2022 - day 28 Style Transfer Image gradients; Style Transfer image style features images things class loss dataset kinds network bit function content feature lot level labels examples water correlation From Andrew Fagg 0 likes 1 plays 0
01:16:26 Advanced Machine Learning 2022 - day 26… Advanced Machine Learning 2022 - day 26 Generative Adversarial Networks	Advanced Machine Learning 2022 - day 26 Generative Adversarial Networks Generative Adversarial Networks generator image images discriminator input output things training distribution parameters network idea function sample thing question decoder space side questions From Andrew Fagg 0 likes 4 plays 0
01:13:35 Advanced Machine Learning 2022 - day 25… Advanced Machine Learning 2022 - day 25 Variational Autoencoders	Advanced Machine Learning 2022 - day 25 Variational Autoencoders Variational Autoencoders image space point points images things sigma region representation distribution autoencoder density cats representations function mountains term idea question vector From Andrew Fagg 0 likes 4 plays 0
01:15:37 Advanced Machine Learning 2022 - day 18 Gated… Advanced Machine Learning 2022 - day 18 Gated Recurrent Networks	Advanced Machine Learning 2022 - day 18 Gated Recurrent Networks Gated Recurrent Networks. Hierarchical recurrent networks. things layer network bit dimensionality function point memory inception units idea layers problem kinds unit question convolution input thing gradient From Andrew Fagg 0 likes 4 plays 0
01:14:29 Advanced Machine Learning 2022 - day 17 Recurrent… Advanced Machine Learning 2022 - day 17 Recurrent Neural Networks and Gating	Advanced Machine Learning 2022 - day 17 Recurrent Neural Networks and Gating Homework 4; recurrent neural networks; mathematics of gating output parameters hat bit things function network inception convolution units gradient input lot problem architecture step outputs sequences rotation features From Andrew Fagg 0 likes 2 plays 0
16:47 Introduction to Linear Models - CS 5003 - Diochnos Introduction to Linear Models - CS 5003 - Diochnos	Introduction to Linear Models - CS 5003 - Diochnos perceptron origin points vector naught examples kind point instance perceptrons decision space function classification input sum dimensions rule hypotheses weight From digi0000 Digital Learning 0 likes 4 plays 0
01:17:54 Advanced Machine Learning 2022 - day 14… Advanced Machine Learning 2022 - day 14 Convolutional Neural Netowrks	Advanced Machine Learning 2022 - day 14 Convolutional Neural Netowrks Convolutional neural networks; data augmentation; ImageDataGenerator; creating branching networks tensor input image function convolution things layer output model images object augmentation tensors node class gpu parameters inputs thing rows From Andrew Fagg 0 likes 2 plays 0
01:19:00 Advanced Machine Learning 2022 - Day 13… Advanced Machine Learning 2022 - Day 13 Convolutional Neural Network Architectures	Advanced Machine Learning 2022 - Day 13 Convolutional Neural Network Architectures Convolutional Neural Networks; building image recognition networks; categorical cross-entropy; binary cross-entropy classes image batch rows columns thread max function bit filters class things parameters input generator images layer convolution threads size From Andrew Fagg 0 likes 3 plays 0
22:41 Advanced Machine Learning 2022 - HW3 Code… Advanced Machine Learning 2022 - HW3 Code Discussion	Advanced Machine Learning 2022 - HW3 Code Discussion Zoom Recording ID: 97315189191 UUID: mnFo3jbAQBakR6XILsDh7Q== Meeting Time: 2022-02-28 07:35:29pm validation training images generator homework image function object dataframe bit size things pickle process epoch steps testing test parameters directory From Andrew Fagg 0 likes 3 plays 0
20:30 Advanced Machine Learning 2022 - HW2, part 2 Advanced Machine Learning 2022 - HW2, part 2	Advanced Machine Learning 2022 - HW2, part 2 HW2, part 2 training regularization experiments choice sizes dropout size layer parts models homework function pdf things hyperparameter hyperparameters couple fact vector lambda From Andrew Fagg 0 likes 4 plays 0
12:56 Advanced Machine Learning 2022 - HW2, part 1 Advanced Machine Learning 2022 - HW2, part 1	Advanced Machine Learning 2022 - HW2, part 1 HW2 introduction training size lambda performance choice regularization rotations grid homework hyperparameter validation question experiments cell sizes function respect choices stage layers From Andrew Fagg 0 likes 5 plays 0
01:17:47 Advanced Machine Learning 2022 - day 10… Advanced Machine Learning 2022 - day 10 Regularization and Dropout	Advanced Machine Learning 2022 - day 10 Regularization and Dropout L1 and L2 Regularization, Dropout, including regularization in Keras models training regularization homework dropout bit network function things model size validation questions l1 l2 performance input curve parameters layer neuron From Andrew Fagg 0 likes 5 plays 0
01:09:21 Advanced Machine Learning 2022 - day 09 Training… Advanced Machine Learning 2022 - day 09 Training Larger Models	Advanced Machine Learning 2022 - day 09 Training Larger Models HW1 discussion, the vanishing gradient problem, selecting non-linearities, batch normalization, transfer learning homework training function lot model things batch bit question layer supercomputer thing normalization loss practice parameters distribution problem output metrics From Andrew Fagg 0 likes 1 plays 0
34:57 Advanced Machine Learning 2022 - day 08… Advanced Machine Learning 2022 - day 08 Supplemental HW1 Code	Advanced Machine Learning 2022 - day 08 Supplemental HW1 Code Experiment control code for HW1; Cross-Validation with variations in training set size. training folds bit validation arguments rotation dataset things function parameter homework command shoulder thing dictionary error experiment model outputs exp From Andrew Fagg 0 likes 1 plays 0
01:15:00 Advanced Machine Learning 2022 - day 06… Advanced Machine Learning 2022 - day 06 Implementing DL Experiments	Advanced Machine Learning 2022 - day 06 Implementing DL Experiments Writing python files that are supercomputer-ready; saving/retrieving experiment state to/from pickle files; command-line execution of experiments things training point bit experiments experiment process function arguments questions epochs validation command supercomputer string directory base files history dataset From Andrew Fagg 0 likes 9 plays 0
01:16:55 Advanced Machine Learning 2022 - day 05 First… Advanced Machine Learning 2022 - day 05 First Learning Experiment	Advanced Machine Learning 2022 - day 05 First Learning Experiment Using Jupyter Lab, Building an XOR network layer input units output things point model error network inputs gradient bit direction step parameters pattern function gpu thing epoch From Andrew Fagg 0 likes 16 plays 0