Name Programming Generative AI

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Size 4.03GB

UpdateDate 2024-11-7

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Files Lesson 2 PyTorch for the Impatient/016. 2.15 Linear Regression with PyTorch.mp4 | 129.91MB Introduction/001. Programming Generative AI Introduction.mp4 | 24.87MB Lesson 1 The What, Why, and How of Generative AI/001. Topics.en.srt | 1.09KB Lesson 1 The What, Why, and How of Generative AI/001. Topics.mp4 | 3.83MB Lesson 1 The What, Why, and How of Generative AI/002. 1.1 Generative AI in the Wild.en.srt | 11.85KB Lesson 1 The What, Why, and How of Generative AI/002. 1.1 Generative AI in the Wild.mp4 | 67.53MB Lesson 1 The What, Why, and How of Generative AI/003. 1.2 Defining Generative AI.en.srt | 7.26KB Lesson 1 The What, Why, and How of Generative AI/003. 1.2 Defining Generative AI.mp4 | 23.61MB Lesson 1 The What, Why, and How of Generative AI/004. 1.3 Multitudes of Media.en.srt | 14.92KB Lesson 1 The What, Why, and How of Generative AI/004. 1.3 Multitudes of Media.mp4 | 41.42MB Lesson 1 The What, Why, and How of Generative AI/005. 1.4 How Machines Create.en.srt | 13.85KB Lesson 1 The What, Why, and How of Generative AI/005. 1.4 How Machines Create.mp4 | 49.17MB Lesson 1 The What, Why, and How of Generative AI/006. 1.5 Formalizing Generative Models.en.srt | 16.83KB Lesson 1 The What, Why, and How of Generative AI/006. 1.5 Formalizing Generative Models.mp4 | 56.96MB Lesson 1 The What, Why, and How of Generative AI/007. 1.6 Generative versus Discriminative Models.en.srt | 12.30KB Lesson 1 The What, Why, and How of Generative AI/007. 1.6 Generative versus Discriminative Models.mp4 | 42.33MB Lesson 1 The What, Why, and How of Generative AI/008. 1.7 The Generative Modeling Trilemma.en.srt | 9.24KB Lesson 1 The What, Why, and How of Generative AI/008. 1.7 The Generative Modeling Trilemma.mp4 | 31.20MB Lesson 1 The What, Why, and How of Generative AI/009. 1.8 Introduction to Google Colab.en.srt | 24.45KB Lesson 1 The What, Why, and How of Generative AI/009. 1.8 Introduction to Google Colab.mp4 | 115.35MB Lesson 2 PyTorch for the Impatient/001. Topics.en.srt | 1.19KB Lesson 2 PyTorch for the Impatient/001. Topics.mp4 | 4.27MB Lesson 2 PyTorch for the Impatient/002. 2.1 What Is PyTorch.en.srt | 5.17KB Lesson 2 PyTorch for the Impatient/002. 2.1 What Is PyTorch.mp4 | 17.78MB Lesson 2 PyTorch for the Impatient/003. 2.2 The PyTorch Layer Cake.en.srt | 12.47KB Lesson 2 PyTorch for the Impatient/003. 2.2 The PyTorch Layer Cake.mp4 | 36.72MB Lesson 2 PyTorch for the Impatient/004. 2.3 The Deep Learning Software Trilemma.en.srt | 8.06KB Lesson 2 PyTorch for the Impatient/004. 2.3 The Deep Learning Software Trilemma.mp4 | 24.00MB Lesson 2 PyTorch for the Impatient/005. 2.4 What Are Tensors, Really.en.srt | 6.37KB Lesson 2 PyTorch for the Impatient/005. 2.4 What Are Tensors, Really.mp4 | 22.42MB Lesson 2 PyTorch for the Impatient/006. 2.5 Tensors in PyTorch.en.srt | 11.12KB Lesson 2 PyTorch for the Impatient/006. 2.5 Tensors in PyTorch.mp4 | 38.73MB Lesson 2 PyTorch for the Impatient/007. 2.6 Introduction to Computational Graphs.en.srt | 15.60KB Lesson 2 PyTorch for the Impatient/007. 2.6 Introduction to Computational Graphs.mp4 | 25.07MB Lesson 2 PyTorch for the Impatient/008. 2.7 Backpropagation Is Just the Chain Rule.en.srt | 20.87KB Lesson 2 PyTorch for the Impatient/008. 2.7 Backpropagation Is Just the Chain Rule.mp4 | 34.72MB Lesson 2 PyTorch for the Impatient/009. 2.8 Effortless Backpropagation with torch.autograd.en.srt | 14.89KB Lesson 2 PyTorch for the Impatient/009. 2.8 Effortless Backpropagation with torch.autograd.mp4 | 55.79MB Lesson 2 PyTorch for the Impatient/010. 2.9 PyTorch's Device Abstraction (i.e., GPUs).en.srt | 5.05KB Lesson 2 PyTorch for the Impatient/010. 2.9 PyTorch's Device Abstraction (i.e., GPUs).mp4 | 12.40MB Lesson 2 PyTorch for the Impatient/011. 2.10 Working with Devices.en.srt | 12.30KB Lesson 2 PyTorch for the Impatient/011. 2.10 Working with Devices.mp4 | 53.56MB Lesson 2 PyTorch for the Impatient/012. 2.11 Components of a Learning Algorithm.en.srt | 8.88KB Lesson 2 PyTorch for the Impatient/012. 2.11 Components of a Learning Algorithm.mp4 | 23.35MB Lesson 2 PyTorch for the Impatient/013. 2.12 Introduction to Gradient Descent.en.srt | 7.21KB Lesson 2 PyTorch for the Impatient/013. 2.12 Introduction to Gradient Descent.mp4 | 24.20MB Lesson 2 PyTorch for the Impatient/014. 2.13 Getting to Stochastic Gradient Descent (SGD).en.srt | 5.40KB Lesson 2 PyTorch for the Impatient/014. 2.13 Getting to Stochastic Gradient Descent (SGD).mp4 | 15.00MB Lesson 2 PyTorch for the Impatient/015. 2.14 Comparing Gradient Descent and SGD.en.srt | 7.17KB Lesson 2 PyTorch for the Impatient/015. 2.14 Comparing Gradient Descent and SGD.mp4 | 29.22MB Lesson 2 PyTorch for the Impatient/016. 2.15 Linear Regression with PyTorch.en.srt | 29.13KB Introduction/001. Programming Generative AI Introduction.en.srt | 8.00KB Lesson 2 PyTorch for the Impatient/017. 2.16 Perceptrons and Neurons.en.srt | 9.01KB Lesson 2 PyTorch for the Impatient/017. 2.16 Perceptrons and Neurons.mp4 | 31.42MB Lesson 2 PyTorch for the Impatient/018. 2.17 Layers and Activations with torch.nn.en.srt | 13.97KB Lesson 2 PyTorch for the Impatient/018. 2.17 Layers and Activations with torch.nn.mp4 | 62.29MB Lesson 2 PyTorch for the Impatient/019. 2.18 Multi-layer Feedforward Neural Networks (MLP).en.srt | 9.90KB Lesson 2 PyTorch for the Impatient/019. 2.18 Multi-layer Feedforward Neural Networks (MLP).mp4 | 46.68MB Lesson 3 Latent Space Rules Everything Around Me/001. Topics.en.srt | 1.15KB Lesson 3 Latent Space Rules Everything Around Me/001. Topics.mp4 | 4.54MB Lesson 3 Latent Space Rules Everything Around Me/002. 3.1 Representing Images as Tensors.en.srt | 10.03KB Lesson 3 Latent Space Rules Everything Around Me/002. 3.1 Representing Images as Tensors.mp4 | 35.04MB Lesson 3 Latent Space Rules Everything Around Me/003. 3.2 Desiderata for Computer Vision.en.srt | 6.19KB Lesson 3 Latent Space Rules Everything Around Me/003. 3.2 Desiderata for Computer Vision.mp4 | 22.46MB Lesson 3 Latent Space Rules Everything Around Me/004. 3.3 Features of Convolutional Neural Networks.en.srt | 9.49KB Lesson 3 Latent Space Rules Everything Around Me/004. 3.3 Features of Convolutional Neural Networks.mp4 | 29.83MB Lesson 3 Latent Space Rules Everything Around Me/005. 3.4 Working with Images in Python.en.srt | 13.30KB Lesson 3 Latent Space Rules Everything Around Me/005. 3.4 Working with Images in Python.mp4 | 51.03MB Lesson 3 Latent Space Rules Everything Around Me/006. 3.5 The FashionMNIST Dataset.en.srt | 5.68KB Lesson 3 Latent Space Rules Everything Around Me/006. 3.5 The FashionMNIST Dataset.mp4 | 16.92MB Lesson 3 Latent Space Rules Everything Around Me/007. 3.6 Convolutional Neural Networks in PyTorch.en.srt | 14.20KB Lesson 3 Latent Space Rules Everything Around Me/007. 3.6 Convolutional Neural Networks in PyTorch.mp4 | 40.25MB Lesson 3 Latent Space Rules Everything Around Me/008. 3.7 Components of a Latent Variable Model (LVM).en.srt | 10.65KB Lesson 3 Latent Space Rules Everything Around Me/008. 3.7 Components of a Latent Variable Model (LVM).mp4 | 36.54MB Lesson 3 Latent Space Rules Everything Around Me/009. 3.8 The Humble Autoencoder.en.srt | 6.64KB Lesson 3 Latent Space Rules Everything Around Me/009. 3.8 The Humble Autoencoder.mp4 | 19.92MB Lesson 3 Latent Space Rules Everything Around Me/010. 3.9 Defining an Autoencoder with PyTorch.en.srt | 7.12KB Lesson 3 Latent Space Rules Everything Around Me/010. 3.9 Defining an Autoencoder with PyTorch.mp4 | 20.11MB Lesson 3 Latent Space Rules Everything Around Me/011. 3.10 Setting up a Training Loop.en.srt | 11.86KB Lesson 3 Latent Space Rules Everything Around Me/011. 3.10 Setting up a Training Loop.mp4 | 33.95MB Lesson 3 Latent Space Rules Everything Around Me/012. 3.11 Inference with an Autoencoder.en.srt | 5.67KB Lesson 3 Latent Space Rules Everything Around Me/012. 3.11 Inference with an Autoencoder.mp4 | 18.12MB Lesson 3 Latent Space Rules Everything Around Me/013. 3.12 Look Ma, No Features!.en.srt | 11.04KB Lesson 3 Latent Space Rules Everything Around Me/013. 3.12 Look Ma, No Features!.mp4 | 32.93MB Lesson 3 Latent Space Rules Everything Around Me/014. 3.13 Adding Probability to Autoencoders (VAE).en.srt | 6.22KB Lesson 3 Latent Space Rules Everything Around Me/014. 3.13 Adding Probability to Autoencoders (VAE).mp4 | 17.57MB Lesson 3 Latent Space Rules Everything Around Me/015. 3.14 Variational Inference Not Just for Autoencoders.en.srt | 9.41KB Lesson 3 Latent Space Rules Everything Around Me/015. 3.14 Variational Inference Not Just for Autoencoders.mp4 | 28.92MB Lesson 3 Latent Space Rules Everything Around Me/016. 3.15 Transforming an Autoencoder into a VAE.en.srt | 18.01KB Lesson 3 Latent Space Rules Everything Around Me/016. 3.15 Transforming an Autoencoder into a VAE.mp4 | 34.86MB Lesson 3 Latent Space Rules Everything Around Me/017. 3.16 Training a VAE with PyTorch.en.srt | 19.39KB Lesson 3 Latent Space Rules Everything Around Me/017. 3.16 Training a VAE with PyTorch.mp4 | 35.49MB Lesson 3 Latent Space Rules Everything Around Me/018. 3.17 Exploring Latent Space.en.srt | 16.57KB Lesson 3 Latent Space Rules Everything Around Me/018. 3.17 Exploring Latent Space.mp4 | 40.63MB Lesson 3 Latent Space Rules Everything Around Me/019. 3.18 Latent Space Interpolation and Attribute Vectors.en.srt | 18.05KB Lesson 3 Latent Space Rules Everything Around Me/019. 3.18 Latent Space Interpolation and Attribute Vectors.mp4 | 37.49MB Lesson 4 Demystifying Diffusion/001. Topics.en.srt | 1.23KB Lesson 4 Demystifying Diffusion/001. Topics.mp4 | 4.52MB Lesson 4 Demystifying Diffusion/002. 4.1 Generation as a Reversible Process.en.srt | 6.31KB Lesson 4 Demystifying Diffusion/002. 4.1 Generation as a Reversible Process.mp4 | 17.29MB Lesson 4 Demystifying Diffusion/003. 4.2 Sampling as Iterative Denoising.en.srt | 5.41KB Lesson 4 Demystifying Diffusion/003. 4.2 Sampling as Iterative Denoising.mp4 | 19.96MB Lesson 4 Demystifying Diffusion/004. 4.3 Diffusers and the Hugging Face Ecosystem.en.srt | 8.57KB Lesson 4 Demystifying Diffusion/004. 4.3 Diffusers and the Hugging Face Ecosystem.mp4 | 34.64MB Lesson 4 Demystifying Diffusion/005. 4.4 Generating Images with Diffusers Pipelines.en.srt | 35.89KB Lesson 4 Demystifying Diffusion/005. 4.4 Generating Images with Diffusers Pipelines.mp4 | 97.61MB Lesson 4 Demystifying Diffusion/006. 4.5 Deconstructing the Diffusion Process.en.srt | 24.94KB Lesson 4 Demystifying Diffusion/006. 4.5 Deconstructing the Diffusion Process.mp4 | 81.29MB Lesson 4 Demystifying Diffusion/007. 4.6 Forward Process as Encoder.en.srt | 21.75KB Lesson 4 Demystifying Diffusion/007. 4.6 Forward Process as Encoder.mp4 | 67.45MB Lesson 4 Demystifying Diffusion/008. 4.7 Reverse Process as Decoder.en.srt | 9.63KB Lesson 4 Demystifying Diffusion/008. 4.7 Reverse Process as Decoder.mp4 | 28.51MB Lesson 4 Demystifying Diffusion/009. 4.8 Interpolating Diffusion Models.en.srt | 12.18KB Lesson 4 Demystifying Diffusion/009. 4.8 Interpolating Diffusion Models.mp4 | 49.31MB Lesson 4 Demystifying Diffusion/010. 4.9 Image-to-Image Translation with SDEdit.en.srt | 9.75KB Lesson 4 Demystifying Diffusion/010. 4.9 Image-to-Image Translation with SDEdit.mp4 | 27.56MB Lesson 4 Demystifying Diffusion/011. 4.10 Image Restoration and Enhancement.en.srt | 14.40KB Lesson 4 Demystifying Diffusion/011. 4.10 Image Restoration and Enhancement.mp4 | 38.06MB Lesson 5 Generating and Encoding Text with Transformers/001. Topics.en.srt | 1.18KB Lesson 5 Generating and Encoding Text with Transformers/001. Topics.mp4 | 4.01MB Lesson 5 Generating and Encoding Text with Transformers/002. 5.1 The Natural Language Processing Pipeline.en.srt | 16.91KB Lesson 5 Generating and Encoding Text with Transformers/002. 5.1 The Natural Language Processing Pipeline.mp4 | 44.54MB Lesson 5 Generating and Encoding Text with Transformers/003. 5.2 Generative Models of Language.en.srt | 12.18KB Lesson 5 Generating and Encoding Text with Transformers/003. 5.2 Generative Models of Language.mp4 | 39.80MB Lesson 5 Generating and Encoding Text with Transformers/004. 5.3 Generating Text with Transformers Pipelines.en.srt | 19.70KB Lesson 5 Generating and Encoding Text with Transformers/004. 5.3 Generating Text with Transformers Pipelines.mp4 | 48.10MB Lesson 5 Generating and Encoding Text with Transformers/005. 5.4 Deconstructing Transformers Pipelines.en.srt | 10.49KB Lesson 5 Generating and Encoding Text with Transformers/005. 5.4 Deconstructing Transformers Pipelines.mp4 | 30.54MB Lesson 5 Generating and Encoding Text with Transformers/006. 5.5 Decoding Strategies.en.srt | 17.28KB Lesson 5 Generating and Encoding Text with Transformers/006. 5.5 Decoding Strategies.mp4 | 37.70MB Lesson 5 Generating and Encoding Text with Transformers/007. 5.6 Transformers are Just Latent Variable Models for Sequences.en.srt | 16.49KB Lesson 5 Generating and Encoding Text with Transformers/007. 5.6 Transformers are Just Latent Variable Models for Sequences.mp4 | 42.94MB Lesson 5 Generating and Encoding Text with Transformers/008. 5.7 Visualizing and Understanding Attention.en.srt | 31.79KB Lesson 5 Generating and Encoding Text with Transformers/008. 5.7 Visualizing and Understanding Attention.mp4 | 56.29MB Lesson 5 Generating and Encoding Text with Transformers/009. 5.8 Turning Words into Vectors.en.srt | 13.41KB Lesson 5 Generating and Encoding Text with Transformers/009. 5.8 Turning Words into Vectors.mp4 | 51.75MB Lesson 5 Generating and Encoding Text with Transformers/010. 5.9 The Vector Space Model.en.srt | 9.39KB Lesson 5 Generating and Encoding Text with Transformers/010. 5.9 The Vector Space Model.mp4 | 24.15MB Lesson 5 Generating and Encoding Text with Transformers/011. 5.10 Embedding Sequences with Transformers.en.srt | 13.09KB Lesson 5 Generating and Encoding Text with Transformers/011. 5.10 Embedding Sequences with Transformers.mp4 | 30.25MB Lesson 5 Generating and Encoding Text with Transformers/012. 5.11 Computing the Similarity Between Embeddings.en.srt | 9.33KB Lesson 5 Generating and Encoding Text with Transformers/012. 5.11 Computing the Similarity Between Embeddings.mp4 | 23.57MB Lesson 5 Generating and Encoding Text with Transformers/013. 5.12 Semantic Search with Embeddings.en.srt | 8.24KB Lesson 5 Generating and Encoding Text with Transformers/013. 5.12 Semantic Search with Embeddings.mp4 | 23.30MB Lesson 5 Generating and Encoding Text with Transformers/014. 5.13 Contrastive Embeddings with Sentence Transformers.en.srt | 8.73KB Lesson 5 Generating and Encoding Text with Transformers/014. 5.13 Contrastive Embeddings with Sentence Transformers.mp4 | 20.23MB Lesson 6 Connecting Text and Images/001. Topics.en.srt | 1.11KB Lesson 6 Connecting Text and Images/001. Topics.mp4 | 4.22MB Lesson 6 Connecting Text and Images/002. 6.1 Components of a Multimodal Model.en.srt | 6.89KB Lesson 6 Connecting Text and Images/002. 6.1 Components of a Multimodal Model.mp4 | 16.06MB Lesson 6 Connecting Text and Images/003. 6.2 Vision-Language Understanding.en.srt | 12.46KB Lesson 6 Connecting Text and Images/003. 6.2 Vision-Language Understanding.mp4 | 38.14MB Lesson 6 Connecting Text and Images/004. 6.3 Contrastive Language-Image Pretraining.en.srt | 7.51KB Lesson 6 Connecting Text and Images/004. 6.3 Contrastive Language-Image Pretraining.mp4 | 20.81MB Lesson 6 Connecting Text and Images/005. 6.4 Embedding Text and Images with CLIP.en.srt | 18.96KB Lesson 6 Connecting Text and Images/005. 6.4 Embedding Text and Images with CLIP.mp4 | 41.24MB Lesson 6 Connecting Text and Images/006. 6.5 Zero-Shot Image Classification with CLIP.en.srt | 4.66KB Lesson 6 Connecting Text and Images/006. 6.5 Zero-Shot Image Classification with CLIP.mp4 | 11.95MB Lesson 6 Connecting Text and Images/007. 6.6 Semantic Image Search with CLIP.en.srt | 14.19KB Lesson 6 Connecting Text and Images/007. 6.6 Semantic Image Search with CLIP.mp4 | 40.90MB Lesson 6 Connecting Text and Images/008. 6.7 Conditional Generative Models.en.srt | 6.71KB Lesson 6 Connecting Text and Images/008. 6.7 Conditional Generative Models.mp4 | 24.74MB Lesson 6 Connecting Text and Images/009. 6.8 Introduction to Latent Diffusion Models.en.srt | 10.96KB Lesson 6 Connecting Text and Images/009. 6.8 Introduction to Latent Diffusion Models.mp4 | 33.43MB Lesson 6 Connecting Text and Images/010. 6.9 The Latent Diffusion Model Architecture.en.srt | 7.10KB Lesson 6 Connecting Text and Images/010. 6.9 The Latent Diffusion Model Architecture.mp4 | 23.43MB Lesson 6 Connecting Text and Images/011. 6.10 Failure Modes and Additional Tools.en.srt | 8.67KB Lesson 6 Connecting Text and Images/011. 6.10 Failure Modes and Additional Tools.mp4 | 29.20MB Lesson 6 Connecting Text and Images/012. 6.11 Stable Diffusion Deconstructed.en.srt | 15.57KB Lesson 6 Connecting Text and Images/012. 6.11 Stable Diffusion Deconstructed.mp4 | 37.80MB Lesson 6 Connecting Text and Images/013. 6.12 Writing Our Own Stable Diffusion Pipeline.en.srt | 14.58KB Lesson 6 Connecting Text and Images/013. 6.12 Writing Our Own Stable Diffusion Pipeline.mp4 | 31.76MB Lesson 6 Connecting Text and Images/014. 6.13 Decoding Images from the Stable Diffusion Latent Space.en.srt | 5.51KB Lesson 6 Connecting Text and Images/014. 6.13 Decoding Images from the Stable Diffusion Latent Space.mp4 | 14.03MB Lesson 6 Connecting Text and Images/015. 6.14 Improving Generation with Guidance.en.srt | 11.94KB Lesson 6 Connecting Text and Images/015. 6.14 Improving Generation with Guidance.mp4 | 26.07MB Lesson 6 Connecting Text and Images/016. 6.15 Playing with Prompts.en.srt | 40.44KB Lesson 6 Connecting Text and Images/016. 6.15 Playing with Prompts.mp4 | 120.71MB Lesson 7 Post-Training Procedures for Diffusion Models/001. Topics.en.srt | 1.02KB Lesson 7 Post-Training Procedures for Diffusion Models/001. Topics.mp4 | 4.25MB Lesson 7 Post-Training Procedures for Diffusion Models/002. 7.1 Methods and Metrics for Evaluating Generative AI.en.srt | 8.30KB Lesson 7 Post-Training Procedures for Diffusion Models/002. 7.1 Methods and Metrics for Evaluating Generative AI.mp4 | 22.35MB Lesson 7 Post-Training Procedures for Diffusion Models/003. 7.2 Manual Evaluation of Stable Diffusion with DrawBench.en.srt | 18.57KB Lesson 7 Post-Training Procedures for Diffusion Models/003. 7.2 Manual Evaluation of Stable Diffusion with DrawBench.mp4 | 54.21MB Lesson 7 Post-Training Procedures for Diffusion Models/004. 7.3 Quantitative Evaluation of Diffusion Models with Human Preference Predictors.en.srt | 24.92KB Lesson 7 Post-Training Procedures for Diffusion Models/004. 7.3 Quantitative Evaluation of Diffusion Models with Human Preference Predictors.mp4 | 63.47MB Lesson 7 Post-Training Procedures for Diffusion Models/005. 7.4 Overview of Methods for Fine-Tuning Diffusion Models.en.srt | 11.69KB Lesson 7 Post-Training Procedures for Diffusion Models/005. 7.4 Overview of Methods for Fine-Tuning Diffusion Models.mp4 | 22.83MB Lesson 7 Post-Training Procedures for Diffusion Models/006. 7.5 Sourcing and Preparing Image Datasets for Fine-Tuning.en.srt | 10.05KB Lesson 7 Post-Training Procedures for Diffusion Models/006. 7.5 Sourcing and Preparing Image Datasets for Fine-Tuning.mp4 | 23.58MB Lesson 7 Post-Training Procedures for Diffusion Models/007. 7.6 Generating Automatic Captions with BLIP-2.en.srt | 10.53KB Lesson 7 Post-Training Procedures for Diffusion Models/007. 7.6 Generating Automatic Captions with BLIP-2.mp4 | 21.46MB Lesson 7 Post-Training Procedures for Diffusion Models/008. 7.7 Parameter Efficient Fine-Tuning with LoRA.en.srt | 15.39KB Lesson 7 Post-Training Procedures for Diffusion Models/008. 7.7 Parameter Efficient Fine-Tuning with LoRA.mp4 | 45.43MB Lesson 7 Post-Training Procedures for Diffusion Models/009. 7.8 Inspecting the Results of Fine-Tuning.en.srt | 6.43KB Lesson 7 Post-Training Procedures for Diffusion Models/009. 7.8 Inspecting the Results of Fine-Tuning.mp4 | 16.02MB Lesson 7 Post-Training Procedures for Diffusion Models/010. 7.9 Inference with LoRAs for Style-Specific Generation.en.srt | 15.77KB Lesson 7 Post-Training Procedures for Diffusion Models/010. 7.9 Inference with LoRAs for Style-Specific Generation.mp4 | 42.53MB Lesson 7 Post-Training Procedures for Diffusion Models/011. 7.10 Conceptual Overview of Textual Inversion.en.srt | 9.63KB Lesson 7 Post-Training Procedures for Diffusion Models/011. 7.10 Conceptual Overview of Textual Inversion.mp4 | 33.09MB Lesson 7 Post-Training Procedures for Diffusion Models/012. 7.11 Subject-Specific Personalization with Dreambooth.en.srt | 9.49KB Lesson 7 Post-Training Procedures for Diffusion Models/012. 7.11 Subject-Specific Personalization with Dreambooth.mp4 | 33.14MB Lesson 7 Post-Training Procedures for Diffusion Models/013. 7.12 Dreambooth versus LoRA Fine-Tuning.en.srt | 7.88KB Lesson 7 Post-Training Procedures for Diffusion Models/013. 7.12 Dreambooth versus LoRA Fine-Tuning.mp4 | 22.83MB Lesson 7 Post-Training Procedures for Diffusion Models/014. 7.13 Dreambooth Fine-Tuning with Hugging Face.en.srt | 17.76KB Lesson 7 Post-Training Procedures for Diffusion Models/014. 7.13 Dreambooth Fine-Tuning with Hugging Face.mp4 | 47.62MB Lesson 7 Post-Training Procedures for Diffusion Models/015. 7.14 Inference with Dreambooth to Create Personalized AI Avatars.en.srt | 17.70KB Lesson 7 Post-Training Procedures for Diffusion Models/015. 7.14 Inference with Dreambooth to Create Personalized AI Avatars.mp4 | 51.16MB Lesson 7 Post-Training Procedures for Diffusion Models/016. 7.15 Adding Conditional Control to Text-to-Image Diffusion Models.en.srt | 5.46KB Lesson 7 Post-Training Procedures for Diffusion Models/016. 7.15 Adding Conditional Control to Text-to-Image Diffusion Models.mp4 | 16.30MB Lesson 7 Post-Training Procedures for Diffusion Models/017. 7.16 Creating Edge and Depth Maps for Conditioning.en.srt | 19.98KB Lesson 7 Post-Training Procedures for Diffusion Models/017. 7.16 Creating Edge and Depth Maps for Conditioning.mp4 | 58.39MB Lesson 7 Post-Training Procedures for Diffusion Models/018. 7.17 Depth and Edge-Guided Stable Diffusion with ControlNet.en.srt | 22.31KB Lesson 7 Post-Training Procedures for Diffusion Models/018. 7.17 Depth and Edge-Guided Stable Diffusion with ControlNet.mp4 | 68.81MB Lesson 7 Post-Training Procedures for Diffusion Models/019. 7.18 Understanding and Experimenting with ControlNet Parameters.en.srt | 11.14KB Lesson 7 Post-Training Procedures for Diffusion Models/019. 7.18 Understanding and Experimenting with ControlNet Parameters.mp4 | 35.82MB Lesson 7 Post-Training Procedures for Diffusion Models/020. 7.19 Generative Text Effects with Font Depth Maps.en.srt | 3.57KB Lesson 7 Post-Training Procedures for Diffusion Models/020. 7.19 Generative Text Effects with Font Depth Maps.mp4 | 7.07MB Lesson 7 Post-Training Procedures for Diffusion Models/021. 7.20 Few Step Generation with Adversarial Diffusion Distillation (ADD).en.srt | 8.48KB Lesson 7 Post-Training Procedures for Diffusion Models/021. 7.20 Few Step Generation with Adversarial Diffusion Distillation (ADD).mp4 | 33.79MB Lesson 7 Post-Training Procedures for Diffusion Models/022. 7.21 Reasons to Distill.en.srt | 7.42KB Lesson 7 Post-Training Procedures for Diffusion Models/022. 7.21 Reasons to Distill.mp4 | 18.06MB Lesson 7 Post-Training Procedures for Diffusion Models/023. 7.22 Comparing SDXL and SDXL Turbo.en.srt | 16.03KB Lesson 7 Post-Training Procedures for Diffusion Models/023. 7.22 Comparing SDXL and SDXL Turbo.mp4 | 37.58MB Lesson 7 Post-Training Procedures for Diffusion Models/024. 7.23 Text-Guided Image-to-Image Translation.en.srt | 22.42KB Lesson 7 Post-Training Procedures for Diffusion Models/024. 7.23 Text-Guided Image-to-Image Translation.mp4 | 72.66MB Lesson 7 Post-Training Procedures for Diffusion Models/025. 7.24 Video-Driven Frame-by-Frame Generation with SDXL Turbo.en.srt | 15.99KB Lesson 7 Post-Training Procedures for Diffusion Models/025. 7.24 Video-Driven Frame-by-Frame Generation with SDXL Turbo.mp4 | 78.73MB Lesson 7 Post-Training Procedures for Diffusion Models/026. 7.25 Near Real-Time Inference with PyTorch Performance Optimizations.en.srt | 13.87KB Lesson 7 Post-Training Procedures for Diffusion Models/026. 7.25 Near Real-Time Inference with PyTorch Performance Optimizations.mp4 | 32.17MB Summary/001. Programming Generative AI Summary.en.srt | 1.38KB Summary/001. Programming Generative AI Summary.mp4 | 4.81MB