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دسته بندی دوره ها

Generative AI, from GANs to CLIP, with Python and Pytorch

سرفصل های دوره

Learn to code with the most creative and exciting AI architectures, generative AI networks, from basic to advanced


01 - The generative AI revolution
  • 001 The roadmap, from basic to advanced and beyond
  • 002 Javier sends greetings from his spacecraft
  • 003 The generative revolution coming home
  • 004 The present and future of AI is generative
  • 005 Applications of generative AI
  • 006 Latent spaces and representation learning
  • 007 Navigating latent spaces
  • 008 GANS Generative Adversarial Networks
  • 009 Benefits and possibilities of Generative AI
  • 010 Coming home generative AI and human nature
  • 010 images-used-presentation-creative-commons.txt
  • 011 Javier sings a song dedicated to generative AI
  • external-links.txt

  • 02 - Coding a basic generative architecture
  • 001 Javier introduces section 2 from his spacecraft
  • 002 Understanding the battle between generator and discriminator
  • 003 Understanding Cross Entropy in depth
  • 004 Understanding the equation to calculate the discriminator loss
  • 005 Understanding the equation to calculate the generator loss
  • 006 (Optional) Google Colab Tutorial
  • 007 Coding importing libraries and declaring a visualization function
  • 008 Coding hyperparameters and the DataLoader
  • 009 Coding the generator class
  • 010 Coding the discriminator class
  • 011 Coding the optimizer and testing the generator
  • 012 Coding the loss values of generator and discriminator
  • 013 Coding main training loop, discriminator part
  • 014 Coding main training loop, generator and stats
  • 015 Coding running the training
  • 016 Coding results and conclusions
  • 016 basic-gan-generative-a-i-course-by-ideami.zip

  • 03 - Coding an advanced generative architecture
  • 001 Javier introduces section 3 from his spacecraft
  • 002 Challenges and issues of the basic GAN
  • 003 The Wasserstein Loss
  • 004 The Gradient Penalty
  • 005 Coding setting up libraries and parameters
  • 006 Coding Login and setup of the Wandb stats library
  • 007 Coding Beginning the generator
  • 008 Coding Understanding convolutions
  • 009 Coding The generator class
  • 010 Coding The critic class
  • 011 Coding Alternative way to initialize parameters (optional)
  • 012 Coding Loading the CelebA dataset
  • 013 Coding Declaring dataset, dataloader and optimizers
  • 014 Coding the gradient penalty
  • 015 Coding saving and loading checkpoints
  • 016 Coding training loop - critic training
  • 017 Coding training loop - generator training
  • 018 Coding stats and fixing issues
  • 019 Coding reviewing the code before running the training
  • 020 Coding running the training
  • 021 Coding results after a few epochs
  • 022 Coding results after a few more epochs
  • 023 Coding results getting better and better
  • 024 Coding morphing between points in latent space
  • 025 Coding more morphing
  • 025 advanced-gan-generative-a-i-course-by-ideami.zip
  • external-links.txt

  • 04 - Generating images from text by combining two advanced architectures
  • 001 Javier introduces section 4 from his spacecraft
  • 002 Multimodal generation, an incredible adventure
  • 003 Coding importing the libraries
  • 004 Coding helper functions and hyperparameters
  • 005 Coding Setting up the CLIP model
  • 006 Coding Setting up the Generative transformer model
  • 007 Coding Setting up the latent space parameters to be optimized
  • 008 Coding encode the text prompts through CLIP
  • 009 Coding creating crops from the generated image
  • 010 Coding a function to display generated images and crops
  • 011 Coding optimizing the latent space parameters
  • 012 Coding the training loop
  • 013 Coding running the training
  • 014 Coding interpolating between points in the latent space
  • 015 Coding creating a video of the interpolations and general review
  • 016 Coding creating variations of the code
  • 017 Coding Davinci Sfumato Tweaking the code to create a new kind of texture
  • 018 Coding Davinci Sfumato reflecting about the process
  • 018 multimodal-generation-generative-a-i-course-by-ideami.zip
  • 018 solution-to-taming-transformers-issue-section-4.txt
  • 019 Final greetings from the spacecraft
  • 019 advanced-gan-generative-a-i-course-by-ideami.zip
  • 019 basic-gan-generative-a-i-course-by-ideami.zip
  • 019 multimodal-generation-generative-a-i-course-by-ideami.zip
  • 019 solution-to-taming-transformers-issue-section-4.txt

  • 05 - Editing peoples clothes by combining segmentation and generative AI models
  • 001 Intro people's clothes replacement and editing using Generative AI
  • 002 Coding Setting up libraries and the segmentation model
  • 003 Coding Setting up the Stable Diffusion generative model
  • 004 Coding Loading a picture and running the segmentation process to produce masks
  • 005 Coding Visualizing the generated masks
  • 006 Coding Inpainting, running and experimenting with the Stable Diffusion model
  • 007 Coding Guide the segmentation process with text prompts
  • 008 Coding run the generative model in this alternative setup
  • 008 clothes-inpainting-research-case-clipseg.zip
  • 008 clothes-inpainting-research-case-sam-by-ideami.zip
  • 009 Ending of the section
  • 009 clothes-inpainting-research-case-clipseg.zip
  • 009 clothes-inpainting-research-case-sam-by-ideami.zip

  • 06 - Bonus Activating the Generative Model of your own mind
  • 001 A guided visualization experience to exercise the generative model in your head
  • 002 Intro to the journey to the center of the neuron
  • 003 The container, the salty ocean and the 150000 cortical columns
  • 004 Visualizing the pyramidal neuron
  • 005 The Synapse, visualizing the input-output interface
  • 006 Biological vs Artificial Neurons Inputs, Outputs, Speed, etc
  • 007 Learning in biological and artificial neurons
  • 008 Planning, decision making and world models
  • 009 Efficiency sparsity in biological vs artificial networks
  • 010 Consciousness within the neurons
  • 011 The future, towards AGI ASI
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    تاریخ انتشار: 12 آذر 1402
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