TMLS2020
Notes from chat channels
What are people working on?
Nov 16th
Workshops
Topic: Workshop: MLOps & Automation Workshop: Bringing ML to Production in a Few Easy Steps
Time: Nov 16, 2020 09:00 AM Eastern Time (US and Canada)
who: Yaron Haviv https://medium.com/@yaronhaviv
Tools:
- mlrun - lots of end to end demos /demos
- nuclio
- kubeflow
What it gives us:
- CICD for ML
- auditability
- drift
- feature store for meta data, and drift.
Topic: Reaching Lightspeed Data Science: ETL, ML, and Graph with NVIDIA RAPIDS
Time: Nov 16, 2020 11:00 AM Eastern Time (US and Canada)
https://github.com/dask/dask-tutorial
who: Bradley Rees ( from Nvidia )
https://medium.com/rapids-ai/gpu-dashboards-in-jupyter-lab-757b17aae1d5
https://nvidia.github.io/spark-rapids/
file formats:
h5 - for gentic info.
h5ad - compressed annotated version
nica lung
genetic analysis, 2d visualization
UMAP
- https://www.nature.com/articles/s41467-020-15351-4
- https://umap-learn.readthedocs.io/en/latest/basic_usage.html
Managing Data Science in the Enterprise
who:
- Randi J Ludwig , Sr. Manager Applied Data scientist - Dell Technologies
- Joshua Podulska - Chief Data scientist - Domino Data lab.
The age old “discipline” problem. This is not a data science problem and this is not a technology problem, this is a human problem.
"Paved paths"
kathy oneil weapons of math descruction
Nov 17th
Bonus Workshop: How to Automate Machine Learning With GitHub Actions
11:00 am
boring: what is docker? Skipped it.
Black-Box and Glass-Box Explanation in Machine Learning
who: Dave Scharbach
gradient boost decision tree
SHAP vales Shapley
linear model.
use "patrial depndant ploat " to see the effect of one input.
