Classifying images with torch
We learn about transfer learning, input pipelines, and learning rate schedulers, all while using torch to tell apart species of beautiful birds.
We learn about transfer learning, input pipelines, and learning rate schedulers, all while using torch to tell apart species of beautiful birds.
Machine learning advancements lead to new ways to train models, as well as deceive them. This article discusses ways to train and defend against attacks.
This article discusses GPT-2 and BERT models, as well using knowledge distillation to create highly accurate models with fewer parameters than their teachers
What is Attention, and why is it used in state-of-the-art models? This article discusses the types of Attention and walks you through their implementations.
Since the release of ChatGPT, Large language models (LLMs) have received a huge amount of attention in both industry and the media; resulting in an…
Table of Contents CycleGAN: Unpaired Image-to-Image Translation (Part 3) Configuring Your Development Environment Need Help Configuring Your Development Environment? Project Structure Implementing CycleGAN Training Implementing Training Callback Implementing Data Pipeline and Model Training Perform Image-to-Image Translation Summary Citation Information CycleGAN:…
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