article thumbnail

First ODSC Europe 2023 Sessions Announced

ODSC - Open Data Science

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?

article thumbnail

How Axfood enables accelerated machine learning throughout the organization using Amazon SageMaker

AWS Machine Learning Blog

However, there are many clear benefits of modernizing our ML platform and moving to Amazon SageMaker Studio and Amazon SageMaker Pipelines. The model will be approved by designated data scientists to deploy the model for use in production. Furthermore, several new functionalities have been added in an automated fashion to our ML setup.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Up Your Machine Learning Game With These ODSC East 2024 Sessions

ODSC - Open Data Science

Andre Franca | CTO | connectedFlow Join this session to demystify the world of Causal AI, with a focus on understanding cause-and-effect relationships within data to drive optimal decisions. By the end of this session, you’ll have a practical blueprint to efficiently harness feature stores within ML workflows.

article thumbnail

Announcing the First Sessions for ODSC East 2024

ODSC - Open Data Science

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. Both methods can be valuable for businesses and individuals who do not have the skills or resources to develop ML models themselves.

article thumbnail

How Earth.com and Provectus implemented their MLOps Infrastructure with Amazon SageMaker

AWS Machine Learning Blog

They needed a cloud platform and a strategic partner with proven expertise in delivering production-ready AI/ML solutions, to quickly bring EarthSnap to the market. That is where Provectus , an AWS Premier Consulting Partner with competencies in Machine Learning, Data & Analytics, and DevOps, stepped in.

DevOps 94
article thumbnail

Deliver your first ML use case in 8–12 weeks

AWS Machine Learning Blog

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. We recognize that customers have different starting points.

ML 88
article thumbnail

MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

Core features of end-to-end MLOps platforms End-to-end MLOps platforms combine a wide range of essential capabilities and tools, which should include: Data management and preprocessing : Provide capabilities for data ingestion, storage, and preprocessing, allowing you to efficiently manage and prepare data for training and evaluation.