[ FreeCourseWeb.com ] Pytorch - Advanced Deep Learning (Computer Vision, DataAug)

Creation Time	April 17, 2025, 8:04 p.m.
Last Access Time	April 20, 2025, 3:32 p.m.
File Size	1.4 GB
Keywords	DataAug - Deep Pytorch Computer FreeCourseWeb Vision Learning com Advanced
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Total Files	128
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~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/001 Data Science in Numpy - Part1 (Code).mp4 117.8 MB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/002 Mocking SimCLR(Code).mp4 57.6 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/005 CutMix (Code).mp4 54.6 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/001 Image Search(Basic & Cluster).mp4 53.9 MB
~Get Your Files Here !/11 PEARL and NPILD (code)/001 NCE & Memory Bank (Code).mp4 53.2 MB
~Get Your Files Here !/03 Pytorch AutoGrad/001 Pytorch AutoGrad.mp4 44.9 MB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/003 SimClr and Supervised Contrastive Learning (Code).mp4 44.8 MB
~Get Your Files Here !/11 PEARL and NPILD (code)/002 Network and Training NPILD & Pearl (Code).mp4 40.3 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/001 Non-Parametric Instance-level Discrimination & Metric learning approach.mp4 39.3 MB
~Get Your Files Here !/01 Introduction/001 Why Should You Take This Course_.mp4 34.7 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/004 Basic Image Search With pertained Resnet (cifar-10 dataset) (Code).mp4 32.6 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/003 Basic Image Search (Code).mp4 32.5 MB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/003 Data Science in Pytorch - Part 2(Code).mp4 32.4 MB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/001 Supervised Contrastive Learning.mp4 31.0 MB
~Get Your Files Here !/01 Introduction/003 Applications.mp4 30.5 MB
~Get Your Files Here !/03 Pytorch AutoGrad/002 Custom CNN in Pytorch.mp4 30.3 MB
~Get Your Files Here !/10 PEARL/004 PEARL Results.mp4 30.3 MB
~Get Your Files Here !/15 Bonus Lectures/001 Vissl & Albumentations.mp4 30.1 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/006 RandAugment.mp4 28.8 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/008 Non Parametric Softmax (CrossEntropy) (Code).mp4 28.6 MB
~Get Your Files Here !/12 SimCLR/001 SIMCLR Overview.mp4 27.4 MB
~Get Your Files Here !/10 PEARL/001 Self-Supervised Learning of Pretext-Invariant Representations (PEARL) - Part 1.mp4 27.3 MB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/002 Data Science in Pytorch - Part1 (Code).mp4 26.1 MB
~Get Your Files Here !/06 Softmax think out of the box (Hands On)/002 Temperature Scaling & soft softmax (code).mp4 26.0 MB
~Get Your Files Here !/08 JigSaw/002 Network and Training process.mp4 22.6 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/002 CutMix Paper Overview.mp4 22.6 MB
~Get Your Files Here !/06 Softmax think out of the box (Hands On)/001 SoftMax Think out of the box.mp4 22.2 MB
~Get Your Files Here !/07 Prelearing & UVR by Context Prediction (Theory)/003 Results of UVR by Context Prediction.mp4 22.0 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/007 RandAugment (Code).mp4 21.9 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/001 Why Data Augmentation & History.mp4 21.8 MB
~Get Your Files Here !/10 PEARL/003 PEARL Loss.mp4 20.4 MB
~Get Your Files Here !/01 Introduction/004 Course Structure & Important Notes.mp4 19.7 MB
~Get Your Files Here !/01 Introduction/002 Google Colab Setup.mp4 18.9 MB
~Get Your Files Here !/12 SimCLR/002 SIMCLR & Multiview Batch.mp4 18.1 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/005 Cluster Search (Code).mp4 17.6 MB
~Get Your Files Here !/12 SimCLR/003 SimCLR Algorithm and Loss.mp4 16.2 MB
~Get Your Files Here !/08 JigSaw/003 Results of JigSaw.mp4 15.6 MB
~Get Your Files Here !/08 JigSaw/001 Overview of Jigsaw.mp4 15.1 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/003 Results of CutMix.mp4 15.1 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/004 Noise contrastive estimation (NCE) - Part 1.mp4 15.1 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/007 NPILD Result.mp4 14.3 MB
~Get Your Files Here !/15 Bonus Lectures/002 Tips From My Expeience.mp4 14.2 MB
~Get Your Files Here !/15 Bonus Lectures/003 Congratulation & Few More ideas.mp4 13.9 MB
~Get Your Files Here !/07 Prelearing & UVR by Context Prediction (Theory)/002 Overview of Unsupervised Visual Representation Learning by Context Prediction.mp4 13.4 MB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/004 CutMix Algorithm.mp4 11.8 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/002 NPILD Training Process.mp4 11.3 MB
~Get Your Files Here !/10 PEARL/002 PEARL Overview Part 2.mp4 11.1 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/006 NPILD Put it all together.mp4 10.7 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/003 Non Parametric Softmax.mp4 9.3 MB
~Get Your Files Here !/07 Prelearing & UVR by Context Prediction (Theory)/001 Pretext Task.mp4 6.9 MB
~Get Your Files Here !/12 SimCLR/005 Softmax is invariant under translation (Important).mp4 5.9 MB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/005 FULL NCE Loss.mp4 5.1 MB
~Get Your Files Here !/12 SimCLR/004 Training Details.mp4 4.2 MB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/002 Faiss Overview.mp4 4.1 MB
~Get Your Files Here !/06 Softmax think out of the box (Hands On)/003 Summery.mp4 3.3 MB
~Get Your Files Here !/11 PEARL and NPILD (code)/npild_pearl/npild_pearl.ipynb 808.3 KB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/selfsupcon_supcon/selfsupcon_supcon.ipynb 453.4 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/augmentations/cutmix.ipynb 437.5 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/image_search/faiss.ipynb 319.0 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/augmentations/randaug.ipynb 97.2 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/image_search/basic_search_with_resnet_imagenet.ipynb 69.4 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/image_search/basic_img_search_with_pretraied_resnet_trained_with_cifar10.ipynb 66.2 KB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/background/torch_training_process.ipynb 64.0 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/image_search/cluster_search_v1.ipynb 60.4 KB
~Get Your Files Here !/06 Softmax think out of the box (Hands On)/soft_softmax/not_so_soft.ipynb 53.6 KB
~Get Your Files Here !/11 PEARL and NPILD (code)/npild_pearl/mock_npild_pearl.ipynb 35.8 KB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/background/numpy_v1.ipynb 20.4 KB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/001 Data Science in Numpy - Part1 (Code).en.srt 16.8 KB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/selfsupcon_supcon/mock_selfsupcon_loss.ipynb 14.2 KB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/background/torch_v2.ipynb 12.7 KB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/002 Mocking SimCLR(Code).en.srt 11.0 KB
~Get Your Files Here !/11 PEARL and NPILD (code)/001 NCE & Memory Bank (Code).en.srt 10.5 KB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/background/torch_intro.ipynb 9.2 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/005 CutMix (Code).en.srt 8.9 KB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/003 Data Science in Pytorch - Part 2(Code).en.srt 8.1 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/001 Image Search(Basic & Cluster).en.srt 7.9 KB
~Get Your Files Here !/03 Pytorch AutoGrad/001 Pytorch AutoGrad.en.srt 7.5 KB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/003 SimClr and Supervised Contrastive Learning (Code).en.srt 7.5 KB
~Get Your Files Here !/11 PEARL and NPILD (code)/npild_pearl/non_parrametric_softmax_crossentropy.ipynb 7.3 KB
~Get Your Files Here !/10 PEARL/003 PEARL Loss.en.srt 6.8 KB
~Get Your Files Here !/02 Data Science in Numpy & Pytorch (code) - Background/002 Data Science in Pytorch - Part1 (Code).en.srt 6.8 KB
~Get Your Files Here !/03 Pytorch AutoGrad/002 Custom CNN in Pytorch.en.srt 6.7 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/001 Non-Parametric Instance-level Discrimination & Metric learning approach.en.srt 6.7 KB
~Get Your Files Here !/13 SupCon & SimCLR (Code)/001 Supervised Contrastive Learning.en.srt 6.4 KB
~Get Your Files Here !/01 Introduction/001 Why Should You Take This Course_.en.srt 6.4 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/003 Basic Image Search (Code).en.srt 6.2 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/008 Non Parametric Softmax (CrossEntropy) (Code).en.srt 6.0 KB
~Get Your Files Here !/10 PEARL/004 PEARL Results.en.srt 6.0 KB
~Get Your Files Here !/11 PEARL and NPILD (code)/002 Network and Training NPILD & Pearl (Code).en.srt 5.9 KB
~Get Your Files Here !/15 Bonus Lectures/002 Tips From My Expeience.en.srt 5.8 KB
~Get Your Files Here !/06 Softmax think out of the box (Hands On)/001 SoftMax Think out of the box.en.srt 5.2 KB
~Get Your Files Here !/08 JigSaw/002 Network and Training process.en.srt 5.2 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/001 Why Data Augmentation & History.en.srt 5.1 KB
~Get Your Files Here !/10 PEARL/001 Self-Supervised Learning of Pretext-Invariant Representations (PEARL) - Part 1.en.srt 5.1 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/004 Noise contrastive estimation (NCE) - Part 1.en.srt 5.0 KB
~Get Your Files Here !/07 Prelearing & UVR by Context Prediction (Theory)/003 Results of UVR by Context Prediction.en.srt 5.0 KB
~Get Your Files Here !/15 Bonus Lectures/003 Congratulation & Few More ideas.en.srt 4.9 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/006 RandAugment.en.srt 4.8 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/004 Basic Image Search With pertained Resnet (cifar-10 dataset) (Code).en.srt 4.7 KB
~Get Your Files Here !/12 SimCLR/001 SIMCLR Overview.en.srt 4.1 KB
~Get Your Files Here !/06 Softmax think out of the box (Hands On)/002 Temperature Scaling & soft softmax (code).en.srt 4.1 KB
~Get Your Files Here !/12 SimCLR/002 SIMCLR & Multiview Batch.en.srt 4.1 KB
~Get Your Files Here !/01 Introduction/004 Course Structure & Important Notes.en.srt 3.9 KB
~Get Your Files Here !/10 PEARL/002 PEARL Overview Part 2.en.srt 3.9 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/002 CutMix Paper Overview.en.srt 3.8 KB
~Get Your Files Here !/01 Introduction/003 Applications.en.srt 3.8 KB
~Get Your Files Here !/01 Introduction/002 Google Colab Setup.en.srt 3.7 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/002 NPILD Training Process.en.srt 3.6 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/006 NPILD Put it all together.en.srt 3.6 KB
~Get Your Files Here !/15 Bonus Lectures/001 Vissl & Albumentations.en.srt 3.5 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/007 RandAugment (Code).en.srt 3.5 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/003 Non Parametric Softmax.en.srt 3.4 KB
~Get Your Files Here !/12 SimCLR/003 SimCLR Algorithm and Loss.en.srt 3.4 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/005 Cluster Search (Code).en.srt 3.3 KB
~Get Your Files Here !/07 Prelearing & UVR by Context Prediction (Theory)/001 Pretext Task.en.srt 2.9 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/003 Results of CutMix.en.srt 2.8 KB
~Get Your Files Here !/05 SOTA Data augmentation (Hands On)/004 CutMix Algorithm.en.srt 2.7 KB
~Get Your Files Here !/07 Prelearing & UVR by Context Prediction (Theory)/002 Overview of Unsupervised Visual Representation Learning by Context Prediction.en.srt 2.4 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/007 NPILD Result.en.srt 2.4 KB
~Get Your Files Here !/08 JigSaw/003 Results of JigSaw.en.srt 2.2 KB
~Get Your Files Here !/12 SimCLR/005 Softmax is invariant under translation (Important).en.srt 2.2 KB
~Get Your Files Here !/08 JigSaw/001 Overview of Jigsaw.en.srt 2.0 KB
~Get Your Files Here !/12 SimCLR/004 Training Details.en.srt 1.8 KB
~Get Your Files Here !/09 Non-Parametric Instance Level Discrimination(NPILD) (hands on)/005 FULL NCE Loss.en.srt 1.6 KB
~Get Your Files Here !/04 Faiss & Image Search (Hands on)/002 Faiss Overview.en.srt 1.5 KB
~Get Your Files Here !/06 Softmax think out of the box (Hands On)/003 Summery.en.srt 602 bytes
~Get Your Files Here !/Bonus Resources.txt 357 bytes
Get Bonus Downloads Here.url 183 bytes

[ FreeCourseWeb.com ] Pytorch - Advanced Deep Learning (Computer Vision, DataAug)

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