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

Non-Deep Learning modelling techniques are still the bedrock for many ML-powered services today.
Join us as we explore how to create interpretable credit scorecards using XGBoost and forecast electricity prices using LinkedIn Engineering's recently released GreyKite time series forecasting library.

In this webinar deep learning educator, Charles Frye discussed: 
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* Collaboration in unified workspaces
* Managing the visibility of ML projects across teams, stakeholders & academic community
* Visualization in live dashboards for fast experimentation