ODSC - Open Data Science

FEBRUARY 22, 2024

By the end of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows. Using Graphs for Large Feature Engineering Pipelines Wes Madrigal | ML Engineer | Mad Consulting Feature engineering from raw entity-level data is complex, but there are ways to reduce that complexity.

Machine Learning 52

Machine Learning Data Science Python ML 52

ODSC - Open Data Science

MARCH 27, 2023

ML Governance: A Lean Approach Ryan Dawson | Principal Data Engineer | Thoughtworks Meissane Chami | Senior ML Engineer | Thoughtworks During this session, you’ll discuss the day-to-day realities of ML Governance. Some of the questions you’ll explore include How much documentation is appropriate?

Machine Learning 98

Machine Learning Data Ingestion Explainability ML 98

AWS Machine Learning Blog

FEBRUARY 27, 2024

Axfood has a structure with multiple decentralized data science teams with different areas of responsibility. Together with a central data platform team, the data science teams bring innovation and digital transformation through AI and ML solutions to the organization.

Machine Learning 112

Machine Learning DevOps Data Quality Data Scientist 112

ODSC - Open Data Science

JANUARY 10, 2024

Causal AI: from Data to Action Dr. Andre Franca | CTO | connectedFlow Explore the world of Causal AI for data science practitioners, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. Sign me up! Register for ODSC East today to save 60% on any pass.

Large Language Models 52

Large Language Models LLM Deep Learning ML 52

ODSC - Open Data Science

JULY 19, 2023

Machine Learning Operations (MLOps) can significantly accelerate how data scientists and ML engineers meet organizational needs. A well-implemented MLOps process not only expedites the transition from testing to production but also offers ownership, lineage, and historical data about ML artifacts used within the team.

Machine Learning 52

Machine Learning Data Drift Data Science ML Engineer 52

AWS Machine Learning Blog

APRIL 26, 2023

The first is by using low-code or no-code ML services such as Amazon SageMaker Canvas , Amazon SageMaker Data Wrangler , Amazon SageMaker Autopilot , and Amazon SageMaker JumpStart to help data analysts prepare data, build models, and generate predictions. Conduct exploratory analysis and data preparation.

ML 88

ML Machine Learning Data Science Data Drift 88

DataRobot Blog

SEPTEMBER 13, 2022

At this level, the data science team will be small or nonexistent. Businesses will then require more information-literate staff, but they’ll need to contend with an ongoing shortage of data scientists. They work cross-functionally, from data ingestion to model deployment.

Data Scientist 52

Data Scientist Automation ML Data Ingestion 52