Run LLM evaluations right in the W&B Weave UI

Tracking and optimizing agentic workflows using W&B Weave and NVIDIA NeMo Agent Toolkit

The Microsoft Agent Framework: Observability

Make evaluations count: Comparing AI application evaluation results using W&B Weave

Understanding the Effectivity of Ensembles in Deep Learning

Measuring Mode Collapse in GANs Using Weights & Biases

Generate Meaningful Captions for Images With Attention Models

Cute Animals and Post-Modern Style Transfer: StarGAN v2 for Multi-Domain Image Synthesis

Modern Data Augmentation Techniques for Computer Vision

Hiding In Plain Sight: Deep Steganography

GCP with Weights & Biases

Implementing and Tracking the Performance of a CNN in PyTorch

PyTorch Dropout for regularization - tutorial

Plotting Keras History Using Weights & Biases

AI For AG: Production ML for Agriculture Using Weights & Biases

W&B Updates June 12, 2020

Diving Into Model Pruning in Deep Learning

Monitor Your PyTorch Models With Five Extra Lines of Code

Part I: Best Practices for Picking a Machine Learning Model

Learning Dynamics of RNNs, and Memory Augmented RNNs

Visualize LightGBM Performance in One Line of Code

Hyperparameter Tuning for Keras and Pytorch models

DeepChem: Predicting Molecular Solubility With Weights & Biases

DeepForm: Track Political Advertising With Deep Learning