| 1 - Introduction.mp4 | 129.9 MB | ||
| 10 - Reverse process sampling.mp4 | 78.4 MB | ||
| 11 - Reverse process visualization.mp4 | 40.6 MB | ||
| 12 - Training equations part 1.mp4 | 72.7 MB | ||
| 13 - Training equations part 2.mp4 | 81.2 MB | ||
| 14 - Training equations implementation part 1.mp4 | 75.2 MB | ||
| 15 - Training equations implementation part 2.mp4 | 99.6 MB | ||
| 16 - Implementation of the training loop.mp4 | 58.8 MB | ||
| 17 - Training on GPU.mp4 | 86.1 MB | ||
| 18 - Correct typo.mp4 | 10.4 MB | ||
| 19 - Reproduction of a Figure from the paper Analysis of the results.mp4 | 28.8 MB | ||
| 2 - Forward Diffusion process.mp4 | 101.3 MB | ||
| 20 - Review of the paper.mp4 | 275.8 MB | ||
| 21 - Time embedding.mp4 | 47.3 MB | ||
| 22 - Pseudocode.mp4 | 51 MB | ||
| 23 - UNet Implementation time embedding.mp4 | 109.9 MB | ||
| 24 - UNet Implementation downsampling.mp4 | 100.9 MB | ||
| 25 - UNet Implementation upsampling.mp4 | 46.9 MB | ||
| 26 - UNet Implementation ResNet part1.mp4 | 108.1 MB | ||
| 27 - UNet Implementation ResNet part2.mp4 | 160.1 MB | ||
| 28 - UNet Implementation ResNet part3.mp4 | 27.5 MB | ||
| 29 - UNet Implementation Attention Mechanism part1.mp4 | 62.2 MB | ||
| 3 - Forward Diffusion process implementation.mp4 | 116.6 MB | ||
| 30 - UNet Implementation Attention Mechanism part2.mp4 | 9.9 MB | ||
| 31 - Finishing the UNet Implementation part1.mp4 | 156 MB | ||
| 32 - Finishing the UNet Implementation part2.mp4 | 50.1 MB | ||
| 33 - Finishing the UNet Implementation part3.mp4 | 24.1 MB | ||
| 34 - Finishing the UNet Implementation part4.mp4 | 126.7 MB | ||
| 35 - Finishing the UNet Implementation part5.mp4 | 44.2 MB | ||
| 36 - Denoising Diffusion Probabilistic Models implementation.mp4 | 42.8 MB | ||
| 37 - Denoising Diffusion Probabilistic Models training.mp4 | 55.2 MB | ||
| 38 - Denoising Diffusion Probabilistic Models sampling.mp4 | 93.8 MB | ||
| 39 - Denoising Diffusion Probabilistic Models utils.mp4 | 78.6 MB | ||
| 4 - Diffusion process tricks.mp4 | 30 MB | ||
| 40 - Denoising Diffusion Probabilistic Models training loop.mp4 | 38.8 MB | ||
| 41 - Denoising Diffusion Probabilistic Models visualization.mp4 | 54.3 MB | ||
| 42 - Denoising Diffusion Probabilistic Models training on GPU.mp4 | 57.2 MB | ||
| 43 - Analysis of the results.mp4 | 11.6 MB | ||
| 44 - Inpainting with Diffusion Models explanation.mp4 | 97.6 MB | ||
| 45 - Inpainting with Diffusion Models implementation.mp4 | 187.1 MB | ||
| 46 - Animations part1.mp4 | 96.7 MB | ||
| 47 - Animations part2.mp4 | 91.7 MB | ||
| 48 - Animations part3.mp4 | 47.5 MB | ||
| 5 - Diffusion process incorporation of the tricks in the implementation.mp4 | 77.9 MB | ||
| 6 - Diffusion process visualization.mp4 | 69.6 MB | ||
| 7 - Reverse process.mp4 | 58.6 MB | ||
| 8 - Reverse process implementation.mp4 | 30.6 MB | ||
| 9 - Architecture of the model.mp4 | 125.6 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 50 total files | |||
Introduction To Diffusion Models 2023
https://DevCourseWeb.com
Published 5/2023
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.64 GB | Duration: 8h 3m
Diffusion Models from scratch using PyToch | In depth breaking down of Stable Diffusion and DALL-E
What you'll learn
How Diffusion Models work
Implementation of Diffusion Models from scratch using PyTorch
In depth understanding of inpainting with Diffusion Models
Deep analysis of Stable Diffusion: opening the black box
Making great animations with Diffusion Models
Review of impactful research papers
Requirements
Basic programming knowledge
Basic Machine Learning knowledge
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 3.1 GB | freecoursewb | 13 hours | 1 | 3 | |
| 3.8 GB | freecoursewb | 2 weeks | 4 | 5 | |
| 1.6 GB | freecoursewb | 2 weeks | 5 | 3 | |
| 1.6 GB | freecoursewb | 2 weeks | 9 | 4 | |
| 649 MB | freecoursewb | 2 weeks | 10 | 3 |
All Comments