How to Perform Image Augmentation With KerasCV Members Public

Training computer vision models with little data can lead to poor model performance. This problem can be solved by generating new data samples from the existing images. For example, you can create new images by flipping and rotating the existing ones. Generating new image samples from existing ones is known

Derrick Mwiti
Derrick Mwiti
TensorFlow

How to Build LLM Applications With LangChain and Openai Members Public

LangChain is an open-source tool for building large language model (LLM) applications. It supports a variety of open-source and closed models, making it easy to create these applications with one tool. Some of the modules in Langchain include: * Models for supported models and integrations * Prompts for making it easy to

Derrick Mwiti
Derrick Mwiti
llms

How to Train Stable Diffusion With Keras 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

Derrick Mwiti
Derrick Mwiti
TensorFlow

How to Generate Images with Variational Autoencoders(VAE) (Create VAE from scratch using Keras and TensorFlow) 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

Derrick Mwiti
Derrick Mwiti
TensorFlow

Distributed training with TensorFlow: How to train Keras models on multiple GPUs 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

Derrick Mwiti
Derrick Mwiti
TensorFlow

Technical Writing: Ultimate Beginners Guide 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

Derrick Mwiti
Derrick Mwiti
Technical Writing

Writing for Data Scientists 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

Derrick Mwiti
Derrick Mwiti

Create U-Net from scratch (Image segmentation with U-Net with Keras and TensorFlow) 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

Derrick Mwiti
Derrick Mwiti
TensorFlow