This webinar featured: 
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* Best practices on reproducible, organized, and effective NLP
* What a neural network thinks of your
twitter feed
* Contemporary NLP with pre-trained attention-based models
* Features like metric logging, hyperparameter optimization, and artifact tracking

In this session DL engineer, Stacey Svetlichnaya talked about: 
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* How to filter, sort and group metrics interactively in the W&B dashboard
* Sharing results with team members through reports
* W&B benchmarks: SafeLife, DeepForm, DroneDeploy & others

In this session DL engineer, Stacey Svetlichnaya talked about: 
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* Central self-driving subproblems such as semantic segmentation and object detection
* How reports let you organize your work, describe findings, and share updates with colleagues
* Insights applicable to other domains such as medical imaging, satellite data, microscopic slides and more

Rewatch how the audience joined Chris in his live Colab workspace to version datasets in a W&B managed project. You will learn about:
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* Securely recording every version of a dataset
* How entire datasets are stored in Artifacts
* Achievement of rich analysis and governance of your models

It sometimes feels like people doing Machine Learning think that reproducible experiments are a myth.
In this webinar Scott Condron will show how to use W&B to make this easy.

In this webinar guest speaker Markus Weber, Sr. Marketing Manager at NVIDIA and Chris Van Pelt, co-founder of Weights & Biases discussed: 
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* What NVIDIA Base Command Platform is, & why NVIDIA built it
* How it can be used to increase productivity of AI developers & researchers
* How W&B seamlessly adds capabilities to enhance MLOps workflows by effortlessly visualizing, debugging, analyzing and reporting model performance