Watch this on-demand webinar by Anyscale, the company behind Ray, the unified framework for scalable computing, and Weights & Biases, the leading developer-first MLOps platform. The webinar discusses how Ray and Weights & Biases are used together by developers and AI teams to ease AI/ML development, experimentation, experiment tracking, model scaling and model management.
Hear about:
Instant ML workload scaling from a laptop to the cloud
Understand how to scale ML workloads from your laptop to the cloud with no code changes. With a single script prepare data, tune, train and scale your workloads.
Faster developer velocity and experimentation
See how to speed model development and iterations without scaling complexity. Visualize, optimize, collaborate and standardize models and data pipelines.
Reproducible and shareable ML workflows
Learn how to track and ease repeatability of a model architecture, hyper-parameters, weights, model predictions, GPU usage, git commits, and even datasets, to ease experimentation and collaboration.
Large-scale training and tuning
Hear how organizations are benefitting from embarrassingly parallel experiments for use cases including recommendation systems to demand forecasting, logistics and on-time delivery optimization, drug discovery, game balancing and more.
“With very little effort, you can use Ray to write a distributed application and scale it in the cluster - because Ray has very simple and intuitive APIs. Even in a single node, it’s much easier to write a multi-processing application using Ray than using the python multiprocessing library” - Intel
"Weight and Biases is a key piece of our fast-paced, cutting-edge, large-scale research workflow: great flexibility, performance, and user experience." - Toyota