Data-Centric MLOps 4 Step Process

Abstract: 

In this demo, we will discuss:
1. Unlimited Auto Annotation
2. Automatic machine learning (AutoML) + Automatic AI code generation (Magic Code) - Tabular data, Object Detection, Recommendation system support
3. One-click AI model deployment to the major cloud servers or in the GPU server which has a fully tuned inference accelerator system using TensorRT, FastAPI, Redis, ETC.
4. Inference result is automatically saved in the dataset and it can be used to auto annotation to build better accuracy AI models.

Bio: 

Marcus is the Global Technical Sales Specialist for DSLAB GLOBAL. Previously, he worked as a business analyst for a Seoul-based Ed-tech company and sales manager for State Farm Insurance & Financial Services. He has a BS in Biology/Chemistry from Virginia Commonwealth University.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

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