[ DevCourseWeb.com ] Udemy - Advanced Computer Vision Replearning, Vae, Gan, Deepfake +
DevCourseWebUdemyAdvancedComputerVisionReplearningDeepfake
种子大小:1.48 GB
收录时间:2022-12-01
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文件列表:137File
- ~Get Your Files Here !/2 - Data Science in Numpy & Pytorch code Background/5 - Data Science in Numpy Part1 Code.mp459.07 MB
- ~Get Your Files Here !/13 - SupCon & SimCLR Code/51 - Mocking SimCLRCode.mp457.61 MB
- ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/19 - CutMix Code.mp454.55 MB
- ~Get Your Files Here !/4 - Faiss & Image Search Hands on Dont skip/10 - Image SearchBasic & Cluster.mp453.89 MB
- ~Get Your Files Here !/11 - PEARL and NPILD code/43 - NCE & Memory Bank Code.mp453.2 MB
- ~Get Your Files Here !/3 - Pytorch AutoGrad/8 - Pytorch AutoGrad.mp451.09 MB
- ~Get Your Files Here !/16 - DeepFakes & Beyond Second Part of the courseInProgress/57 - Generative Vs Discriminative AI With VAE Example will be separate course.mp450.59 MB
- ~Get Your Files Here !/13 - SupCon & SimCLR Code/52 - SimClr and Supervised Contrastive Learning Code.mp444.83 MB
- ~Get Your Files Here !/11 - PEARL and NPILD code/44 - Network and Training NPILD & Pearl Code.mp440.29 MB
- ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/31 - NonParametric Instancelevel Discrimination & Metric learning approach.mp439.3 MB
- ~Get Your Files Here !/16 - DeepFakes & Beyond Second Part of the courseInProgress/56 - Introduction to DeepFake & Beyond.mp438.69 MB
- ~Get Your Files Here !/4 - Faiss & Image Search Hands on Dont skip/12 - Basic Image Search Code.mp438.61 MB
- ~Get Your Files Here !/1 - Introduction/2 - Applications.mp438.3 MB
- ~Get Your Files Here !/2 - Data Science in Numpy & Pytorch code Background/7 - Data Science in Pytorch Part 2Code.mp438.09 MB
- ~Get Your Files Here !/3 - Pytorch AutoGrad/9 - Custom CNN in Pytorch.mp436.43 MB
- ~Get Your Files Here !/4 - Faiss & Image Search Hands on Dont skip/13 - Basic Image Search With pertained Resnet cifar10 dataset Code.mp432.56 MB
- ~Get Your Files Here !/1 - Introduction/1 - Course Overview.mp431.51 MB
- ~Get Your Files Here !/2 - Data Science in Numpy & Pytorch code Background/6 - Data Science in Pytorch Part1 Code.mp431.5 MB
- ~Get Your Files Here !/6 - Softmax think out of the box Hands On/23 - Temperature Scaling & soft softmax code.mp431.35 MB
- ~Get Your Files Here !/13 - SupCon & SimCLR Code/50 - Supervised Contrastive Learning.mp431.02 MB
- ~Get Your Files Here !/10 - PEARL/42 - PEARL Results.mp430.27 MB
- ~Get Your Files Here !/15 - Few More ideas in Visual Representation Learning/53 - Vissl & Albumentations.mp430.09 MB
- ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/20 - RandAugment.mp428.79 MB
- ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/38 - Non Parametric Softmax CrossEntropy Code.mp428.62 MB
- ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/16 - CutMix Paper Overview.mp428.27 MB
- ~Get Your Files Here !/6 - Softmax think out of the box Hands On/22 - SoftMax Think out of the box.mp427.72 MB
- ~Get Your Files Here !/12 - SimCLR/45 - SIMCLR Overview.mp427.41 MB
- ~Get Your Files Here !/10 - PEARL/39 - SelfSupervised Learning of PretextInvariant Representations PEARL Part 1.mp427.29 MB
- ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/15 - Why Data Augmentation & History.mp426.7 MB
- ~Get Your Files Here !/4 - Faiss & Image Search Hands on Dont skip/14 - Cluster Search Code.mp423.69 MB
- ~Get Your Files Here !/8 - JigSaw/29 - Network and Training process.mp422.65 MB
- ~Get Your Files Here !/7 - Prelearing & UVR by Context Prediction Theory/27 - Results of UVR by Context Prediction.mp421.97 MB
- ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/21 - RandAugment Code.mp421.89 MB
- ~Get Your Files Here !/10 - PEARL/41 - PEARL Loss.mp420.43 MB
- ~Get Your Files Here !/1 - Introduction/4 - Course Structure & Important Notes.mp419.73 MB
- ~Get Your Files Here !/7 - Prelearing & UVR by Context Prediction Theory/26 - Overview of Unsupervised Visual Representation Learning by Context Prediction.mp419.08 MB
- ~Get Your Files Here !/1 - Introduction/3 - Google Colab Setup.mp418.93 MB
- ~Get Your Files Here !/12 - SimCLR/46 - SIMCLR & Multiview Batch.mp418.11 MB
- ~Get Your Files Here !/12 - SimCLR/47 - SimCLR Algorithm and Loss.mp416.21 MB
- ~Get Your Files Here !/8 - JigSaw/30 - Results of JigSaw.mp415.64 MB
- ~Get Your Files Here !/8 - JigSaw/28 - Overview of Jigsaw.mp415.14 MB
- ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/17 - Results of CutMix.mp415.09 MB
- ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/34 - Noise contrastive estimation NCE Part 1.mp415.08 MB
- ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/37 - NPILD Result.mp414.29 MB
- ~Get Your Files Here !/15 - Few More ideas in Visual Representation Learning/54 - Tips From My Expeience.mp414.23 MB
- ~Get Your Files Here !/15 - Few More ideas in Visual Representation Learning/55 - Few More ideas.mp413.88 MB
- ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/18 - CutMix Algorithm.mp411.84 MB
- ~Get Your Files Here !/12 - SimCLR/49 - Softmax is invariant under translation Important.mp411.56 MB
- ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/32 - NPILD Training Process.mp411.3 MB
- ~Get Your Files Here !/10 - PEARL/40 - PEARL Overview Part 2.mp411.11 MB