Class Notes for CS224W (http://web.stanford.edu/class/cs224w/). Made by Anil using Weights & Biases

Explore and run machine learning code with Kaggle Notebooks | Using data from multiple data sources

Explore and run machine learning code with Kaggle Notebooks | Using data from No attached data sources

Run, share, and edit Python notebooks

This article provides a quick tutorial for training Natural Language Processing (NLP) models with HuggingFace and visualizing their performance with W&B.

Explore and run machine learning code with Kaggle Notebooks | Using data from House Prices - Advanced Regression Techniques

In this article, Weights & Biases CEO, Lukas Biewald, gives context to W&B's $45m raise from Insight Partners, and explains his approach and future plans for the company. .

In this article, we explore what causes a neural network to underperform. We also discuss the problem of vanishing and exploding gradients, providing some solutions.

This article summarizes the need for Graph Neural Networks and analyzes one particular architecture – the Gated Graph Convolutional Network.

This article gives a comparison between Cutout, mixup, CutMix, and AugMix augmentations, and their impact on model robustness. .

In this article, we take a look at how to visualize, compare, and iterate on fastai models with Weights & Biases. Made by Boris Dayma using W&B

Weights & Biases, developer tools for machine learning

Colaboratory notebook

In this article, we dissect ensembles in order to provide different insights that are useful for understanding the dynamics of deep neural networks in general.

In this article, we analyze the runtime, energy usage, and performance of Tensorflow training on an M1 Mac Mini and Nvidia V100. .

Publish your model insights with interactive plots for performance metrics, predictions, and hyperparameters. Made by Lavanya Shukla using Weights & Biases

Josh Tobin, a former researcher at OpenAI and creator of Full Stack Deep Learning talks about professionalizing ML workflows for the real world, his work with the Robotics team and FSDL.

Colaboratory notebook

In this article, we demonstrate how to fine-tune a pre-trained HuggingFace Transformer on anyone's Tweets in five minutes. Made by Boris Dayma using W&B

This article explores the ways to distribute your training workloads with minimal code changes and analyze system metrics with Weights & Biases.

Colaboratory notebook

Weights & Biases, developer tools for machine learning

👨🏻‍💻Today our guest is Nicolas Koumchatzky.Nicolas Koumchatzky is the Director of AI infrastructure at NVIDIA, where he's responsible for MagLev, the prod...

Weights & Biases, developer tools for machine learning

This article explores why weight initialization matters, before providing a comparison of a range of weight initialization methods with Weights & Biases.

Why is experiment tracking so important for doing real world machine learning?

Nature Communications - Accurate seasonal forecasts of sea ice are highly valuable, particularly in the context of sea ice loss due to global warming. A new machine learning tool for sea ice...

Supporting the Reproducibility Challenge participants

Weights & Biases, developer tools for machine learning

Job openings at Weights & Biases

Jensen Huang is founder and CEO of NVIDIA, whose GPUs sit at the heart of the majority of machine learning models today.Jensen shares the story behind NVIDIA...

This article introduces supervised contrastive learning, an adaption of contrastive learning in the field of fully supervised learning problems.

This article explores how LSTM works, including how to train them with NumPy, vanish/explode the gradient, and visualize their connectivity. .

This is the first in a series all about real world LLM-app building. Today, we're going to build a customer success ticket classifier and improve its accuracy five fold.

Explore and run machine learning code with Kaggle Notebooks | Using data from Global Wheat Detection