O'Reilly on Data

MARCH 31, 2020

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. A lot to learn, but worthwhile to access the unique and special value AI can create in the product space. Managing Machine Learning Projects” (AWS).

Management 332

Management Machine Learning Experimentation Metrics 332

DataKitchen

APRIL 13, 2021

GitHub – A provider of Internet hosting for software development and version control using Git. AWS Code Commit – A fully-managed source control service that hosts secure Git-based repositories. Azure Repos – Unlimited, cloud-hosted private Git repos. . Acquired by DataRobot June 2019).

Testing 300

Testing Machine Learning Consulting Data Quality 300

Domino Data Lab

JULY 2, 2019

See also: Caroline Lemieux’s slides for that NeurIPS talk, and Rohan Bavishi’s video from the RISE Summer Retreat 2019. The authors of AutoPandas observed that: The APIs for popular data science packages tend to have relatively steep learning curves. Program Synthesis 101 ” – Alexander Vidiborskiy (2019-01-20).

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

Domino Data Lab

MAY 8, 2019

Machine learning model interpretability. At CMU I joined a panel hosted by Zachary Lipton where someone in the audience asked a question about machine learning model interpretation. They also require advanced skills in statistics, experimental design, causal inference, and so on – more than most data science teams will have.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105