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

In this webinar we will use W&B to create a reproducible NLP pipeline.

We will be fine tuning DistilBERT to detect ungrammatical sentences using PyTorch Lightning and HuggingFace, and using W&B to track our model performance, optimize our hyperparameters, and precisely track the inputs and outputs of each stage in our pipeline.

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