Women in Machine Learning Symposium 2021
2021-10-19
-- online --
[Women in Machine Learning Symposium 2021, Women in Machine Learning Symposium 2022]
who it's for
early career machine learning developers, software developers transitioning to machine learning, open source project maintainers, community organizers and meetup leads, diversity and inclusion program leads, engineering managers
topics
TensorFlow certificate program; TensorFlow Developer Professional Certificate; Machine Learning Crash Course; dataset bias and fairness indicators; open source contributor onboarding; measuring noncode contributions; community meetup and affinity groups; deploying models with ONNX to cloud; autoencoder denoising project; dataset caching and data APIs; career negotiation and portfolio building
| title | author | length |
|---|---|---|
| Top takeaways | Joana Carrasqueira | 04m |
The first virtual Women in Machine Learning Symposium brings together women and allies worldwide and reports practical outcomes: improving project… | ||
| Why diversity matters in Machine Learning communities | Jeanine Banks | 10m |
Claims that increasing representation improves product fairness are backed by concrete actions: Google's Image Equity initiative and low light mode for Meet… | ||
| Making OSS Machine Learning communities more diverse | Amanda Casari | 16m |
Argues that counting only repo commits and platform metadata produces a biased picture, cites research showing surveys and pull‑request metrics exclude… | ||
| From being the only woman in the room to empowering the next generation | Joana Carrasqueira, Michelle Carney, Alana Karen, Bianca Ximenes | 34m |
Panel gives concrete, repeatable moves: organized a 60‑person meetup that escalates into visibility and a Google Developer Expert path; affinity groups made… | ||
| How to get started in Machine Learning | Kelsey Schroeder, Irene Giannoumis, Chandni Shah, Merve Noyan | 51m |
Begins with concrete steps: take the Machine Learning Crash Course, build end-to-end projects on GitHub and Kaggle (NLP chatbots and Hugging Face models… | ||
| I'm a developer, how can I become an ML developer? | Megha Malpani, Laura Uzcategui, Margaret Maynard Reid, Nikita Namjoshi | 51m |
Practical roadmap: follow the TensorFlow Developer Professional Certificate (CNNs, NLP, time series) then a deep learning nanodegree with PyTorch and a… | ||
| Gradient ascent for your career | Priya Gupta, Chip Huyen, Laurence Moroney, Jialin Huang, Noelle Silver | 54m |
Claims that AI/ML drives massive job and market growth (37% in data/AI jobs, 40–50% YoY software market, ~100k LinkedIn openings) pair with concrete tooling… | ||
| Get involved in Machine Learning | Carrie Grimes Bostock | 10m |
Argues that increasing diversity in ML matters and gives concrete next steps: integrate responsible AI checks into model workflows, add human reviewers to… | ||
| nothing matches | ||