| Lesson 2 PyTorch for the Impatient/016. 2.15 Linear Regression with PyTorch.mp4 | 129.91 MB |
| Lesson 6 Connecting Text and Images/016. 6.15 Playing with Prompts.mp4 | 120.71 MB |
| Lesson 1 The What, Why, and How of Generative AI/009. 1.8 Introduction to Google Colab.mp4 | 115.35 MB |
| Lesson 4 Demystifying Diffusion/005. 4.4 Generating Images with Diffusers Pipelines.mp4 | 97.61 MB |
| Lesson 4 Demystifying Diffusion/006. 4.5 Deconstructing the Diffusion Process.mp4 | 81.29 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/025. 7.24 Video-Driven Frame-by-Frame Generation with SDXL Turbo.mp4 | 78.73 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/024. 7.23 Text-Guided Image-to-Image Translation.mp4 | 72.66 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/018. 7.17 Depth and Edge-Guided Stable Diffusion with ControlNet.mp4 | 68.81 MB |
| Lesson 1 The What, Why, and How of Generative AI/002. 1.1 Generative AI in the Wild.mp4 | 67.53 MB |
| Lesson 4 Demystifying Diffusion/007. 4.6 Forward Process as Encoder.mp4 | 67.45 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/004. 7.3 Quantitative Evaluation of Diffusion Models with Human Preference Predictors.mp4 | 63.47 MB |
| Lesson 2 PyTorch for the Impatient/018. 2.17 Layers and Activations with torch.nn.mp4 | 62.29 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/017. 7.16 Creating Edge and Depth Maps for Conditioning.mp4 | 58.39 MB |
| Lesson 1 The What, Why, and How of Generative AI/006. 1.5 Formalizing Generative Models.mp4 | 56.96 MB |
| Lesson 5 Generating and Encoding Text with Transformers/008. 5.7 Visualizing and Understanding Attention.mp4 | 56.29 MB |
| Lesson 2 PyTorch for the Impatient/009. 2.8 Effortless Backpropagation with torch.autograd.mp4 | 55.79 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/003. 7.2 Manual Evaluation of Stable Diffusion with DrawBench.mp4 | 54.21 MB |
| Lesson 2 PyTorch for the Impatient/011. 2.10 Working with Devices.mp4 | 53.56 MB |
| Lesson 5 Generating and Encoding Text with Transformers/009. 5.8 Turning Words into Vectors.mp4 | 51.75 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/015. 7.14 Inference with Dreambooth to Create Personalized AI Avatars.mp4 | 51.16 MB |
| Lesson 3 Latent Space Rules Everything Around Me/005. 3.4 Working with Images in Python.mp4 | 51.03 MB |
| Lesson 4 Demystifying Diffusion/009. 4.8 Interpolating Diffusion Models.mp4 | 49.31 MB |
| Lesson 1 The What, Why, and How of Generative AI/005. 1.4 How Machines Create.mp4 | 49.17 MB |
| Lesson 5 Generating and Encoding Text with Transformers/004. 5.3 Generating Text with Transformers Pipelines.mp4 | 48.1 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/014. 7.13 Dreambooth Fine-Tuning with Hugging Face.mp4 | 47.62 MB |
| Lesson 2 PyTorch for the Impatient/019. 2.18 Multi-layer Feedforward Neural Networks (MLP).mp4 | 46.68 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/008. 7.7 Parameter Efficient Fine-Tuning with LoRA.mp4 | 45.43 MB |
| Lesson 5 Generating and Encoding Text with Transformers/002. 5.1 The Natural Language Processing Pipeline.mp4 | 44.54 MB |
| Lesson 5 Generating and Encoding Text with Transformers/007. 5.6 Transformers are Just Latent Variable Models for Sequences.mp4 | 42.94 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/010. 7.9 Inference with LoRAs for Style-Specific Generation.mp4 | 42.53 MB |
| Lesson 1 The What, Why, and How of Generative AI/007. 1.6 Generative versus Discriminative Models.mp4 | 42.33 MB |
| Lesson 1 The What, Why, and How of Generative AI/004. 1.3 Multitudes of Media.mp4 | 41.42 MB |
| Lesson 6 Connecting Text and Images/005. 6.4 Embedding Text and Images with CLIP.mp4 | 41.24 MB |
| Lesson 6 Connecting Text and Images/007. 6.6 Semantic Image Search with CLIP.mp4 | 40.9 MB |
| Lesson 3 Latent Space Rules Everything Around Me/018. 3.17 Exploring Latent Space.mp4 | 40.63 MB |
| Lesson 3 Latent Space Rules Everything Around Me/007. 3.6 Convolutional Neural Networks in PyTorch.mp4 | 40.25 MB |
| Lesson 5 Generating and Encoding Text with Transformers/003. 5.2 Generative Models of Language.mp4 | 39.8 MB |
| Lesson 2 PyTorch for the Impatient/006. 2.5 Tensors in PyTorch.mp4 | 38.73 MB |
| Lesson 6 Connecting Text and Images/003. 6.2 Vision-Language Understanding.mp4 | 38.14 MB |
| Lesson 4 Demystifying Diffusion/011. 4.10 Image Restoration and Enhancement.mp4 | 38.06 MB |
| Lesson 6 Connecting Text and Images/012. 6.11 Stable Diffusion Deconstructed.mp4 | 37.8 MB |
| Lesson 5 Generating and Encoding Text with Transformers/006. 5.5 Decoding Strategies.mp4 | 37.7 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/023. 7.22 Comparing SDXL and SDXL Turbo.mp4 | 37.58 MB |
| Lesson 3 Latent Space Rules Everything Around Me/019. 3.18 Latent Space Interpolation and Attribute Vectors.mp4 | 37.49 MB |
| Lesson 2 PyTorch for the Impatient/003. 2.2 The PyTorch Layer Cake.mp4 | 36.72 MB |
| Lesson 3 Latent Space Rules Everything Around Me/008. 3.7 Components of a Latent Variable Model (LVM).mp4 | 36.54 MB |
| Lesson 7 Post-Training Procedures for Diffusion Models/019. 7.18 Understanding and Experimenting with ControlNet Parameters.mp4 | 35.82 MB |
| Lesson 3 Latent Space Rules Everything Around Me/017. 3.16 Training a VAE with PyTorch.mp4 | 35.49 MB |
| Lesson 3 Latent Space Rules Everything Around Me/002. 3.1 Representing Images as Tensors.mp4 | 35.04 MB |
| Lesson 3 Latent Space Rules Everything Around Me/016. 3.15 Transforming an Autoencoder into a VAE.mp4 | 34.86 MB |