How to Train Stable Diffusion With Keras Paid Members Public
Image generation models are causing a sensation worldwide, particularly the powerful Stable Diffusion technique. With Stable Diffusion, you can generate images with your laptop, which was previously impossible. Here's how diffusion models work in plain English: 1. Generating images involves two processes. Diffusion adds noise gradually to the
How to Generate Images with Variational Autoencoders(VAE) (Create VAE from scratch using Keras and TensorFlow) Paid Members Public
An autoencoder takes an input image and creates a low-dimensional representation, i.e., a latent vector. This vector is then used to reconstruct the original image. Regular autoencoders get an image as input and output the same image. However, Variational AutoEncoders (VAE) generate new images with the same distribution as
Distributed training with TensorFlow: How to train Keras models on multiple GPUs Paid Members Public
Training computer vision models requires a lot of time because of the size of the models and image data. Therefore, training these models can take prolonged periods of time, especially when training on a single GPU. You can reduce the training time by distributing the training across several GPUs. This
Technical Writing: Ultimate Beginners Guide Paid Members Public
I have created technical content for various companies over the last 5 years. Educating developers is how technology companies use to grow their communities. Developers hate being sold to, so this is the best way to get developers to use a company's product. The product should solve a
Writing for Data Scientists Paid Members Public
Download Writing for Data Scientists sample Writing for Data Scientists Free Sample Writing for Data Scientists - Free Sample .pdf337 KBdownload-circle I earned $300 for my first paid data science and machine learning article. I get paid between $250 and $500 for each data science article I write. In this
Create U-Net from scratch (Image segmentation with U-Net with Keras and TensorFlow) Paid Members Public
In the Implementing Fully Convolutional Networks (FCNs) from scratch in Keras and TensorFlow article, you saw how to build an image segmentation model with FCNs. However, due to the model's limitations, it did not perform very well in the segmenting task. In this post, you will see how
Implementing Fully Convolutional Networks (FCNs) from scratch in Keras and TensorFlow (Build image segmentation model from scratch) Paid Members Public
In 2014, Jonathan Long, Evan Shelhamer, and Trevor Darrell proposed solving image segmentation problems using Fully Convolutional Neural Networks(FCNs). FCNs have no fully connected layers. Image segmentation involves making a prediction for each pixel in an image. FCNs can accept images of any size because they don't
How to become a Kaggle Competitions Grandmaster Paid Members Public
writtencast 001 - Shujun He In this inaugural interview of the writtencast, I am joined by Shujun He. Shujun is a P.hD. student at Texas A&M University and a Kaggle Competitions Grandmaster. To become a Kaggle Competitions Grandmaster you need 5 gold medals and at least one
