How Carsales scale up their AI strategy using Metaflow & Amazon SageMaker

Featuring Agustinus Nalwan

Data Products: Hype vs. Reality

Featuring Gwen (Chen) Shapira

Building better and more responsible datasets

Featuring Peter Bailey

Bigger isn't always better and is definitely more likely to be irresponsible when it comes to datasets. But datasets are the unsung heroes of modern machine learning and AI systems, just as much as the algorithms, advanced hardware, and models that support them. In this talk, I share some...

Why Most Data Projects Fail and How to Avoid It

Featuring Jesse Anderson

Unfortunately, the majority of data projects fail. Yet, they fail for the same reasons. Most management and data teams don’t know the reasons a project succeeds or fails. It just appears to be random, hard work, or luck.

Managing Data Pipelines with Conductor

Featuring Doug Sillars

Data pipelines are a challenging part of working in data science. Netflix Conductor is a battle-tested workflow orchestration tool invented at Netflix to automate millions of microservice workflows. Using a workflow tool like Conductor as a part of your data analysis pipeline can help streamline...

Carbon on the agenda

Featuring Louis van Senden

Real-time data engineering and the unified modern data platform

Featuring Eric Sammer

Distributed pandas – long promised, finally sort of

Featuring Holden Karau

Lessons Learned from DAG-based Workflow Orchestration

Featuring Kevin Kho

Workflow orchestration has traditionally been closely coupled to the concept of Directed Acyclic Graphs (DAGs). Building data pipelines involved registering a static graph containing all the tasks and their respective dependencies. During workflow execution, this graph would be traversed and...

Heralding Scientific Breakthroughs Through AI At Supercomputing Scale

Featuring Animashree Anandkumar