Implementing CycleGAN for Age Conversion
In this tutorial we'll train CycleGAN with Keras to generate images which age a subject's face, either forwards or backwards.
5 years ago
Generative Models
Generating an interactive Pix2Pix model with Gradient° and ml5.js
Learn to train a generative image model using Gradient° and then porting the model to ml5.js, so you can interact with it in the browser.
6 years ago
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Quilt
Reproducible machine learning with PyTorch and Quilt
In this article, we'll use Quilt to transfer versioned training data to a remote machine. We'll start with the Berkeley Segmentation Dataset, package the dataset, then train a PyTorch model for super-resolution imaging.
By
Aneesh Karve
Creating your own style transfer mirror with Gradient° and ml5.js
In this post, we will learn how to train a style transfer network with Paperspace's Gradient° and use the model in to create an interactive style transfer mirror.
6 years ago
Training an LSTM network and sampling the resulting model in ml5.js
In this post, we will learn how to train a language model using a LSTM neural network with your own custom dataset and use the resulting model inside so you will able to sample from it directly from the browser!
6 years ago
Building a simple Generative Adversarial Network (GAN) using TensorFlow
Generative Adversarial Networks or GANs are one of the most active areas in deep learning research and development due to their incredible ability to generate synthetic results. In this blog, we will build out the basic intuition of GANs through a concrete example.
By
Aadil Hayat
Generative Models
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Recurrent Language Models with RNNs
In this article, we will first try to understand the basics of language models, what Recurrent Neural Networks are and how can we use them to solve the problem of language modeling.
By
Felipe Ducau
Featured
public
Computer Vision
Adversarial Autoencoders (with Pytorch)
Learn how to build and run an adversarial autoencoder using PyTorch. Solve the problem of unsupervised learning in machine learning.
By
Felipe Ducau
