Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the Discriminator network and the Generator network. GANs have been shown to be powerful generative models and are able to successfully generate new data given a large enough training dataset.
Collection of google colaboratory notebooks for fast and easy experiments
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Notebook for O'Reilly's "Deep Convolutional Generative Adversarial Networks"
Generative Adversarial Networks with TensorFlow2, Keras and Python (Jupyter Notebooks Implementations)
Nvidia DLI workshop on AI-based anomaly detection techniques using GPU-accelerated XGBoost, deep learning-based autoencoders, and generative adversarial networks (GANs) and then implement and compare supervised and unsupervised learning techniques.
An IPython notebook explaining the concepts of Variational Autoencoders and building one using Keras to generate new faces.
Collection of machine learning related notebooks to share.
Small tools, notebooks, code snippets for the Keras Deep Learning library
🌌The Jupyter Notebook behind ThisNightSkyDoesNotExist - Train a StyleGan2-ADA on a custom image dataset scrapped from Instagram!
Gen AI uses GANs to generate CIFAR-10-like images. The custom GAN model comprises a Generator and a Discriminator. Users can train the model and generate images using Jupyter Notebooks or Google Colab.
Deep Learning Projects using Convolutional, Recurrent, and Generative Adversarial Neural Networks.
Here i present several GAN models in format of notebook implemented with tensorflow using the layers API
Course about Generative Adversial Networks and Notebook Tutorial
A PyTorch notebook and implementation of a normal linear GAN
Repository contains notebooks with some AI related problems and sometimes not
Notebooks for sample implementations of a variety of Generative Adversarial Networks
This repository contains notebooks showcasing various generative models, including DCGAN and VAE for anime face generation, an Autoencoder for converting photos to sketches, a captioning model using an attention mechanism for an image caption generator, and more.
This repo contains learnings about Artificial Intelligence and Machine Learning using Python Jupyter Notebooks downloaded as HTML
In this repository I'm implementing PyTorch based Deep Neural Networks from basic ANN to Advanced Graph Neural Networks. Please suggest if you have any ideas
A few Jupyter notebooks on ML for Images
Released June 10, 2014