Smart Data Collective
JUNE 10, 2022
Are you interested in a career in data science? The Bureau of Labor Statistics reports that there are over 105,000 data scientists in the United States. The average data scientist earns over $108,000 a year. Data Scientist. This is the best time ever to pursue this career track.
AWS Machine Learning Blog
MARCH 5, 2025
It requires checking many systems and teams, many of which might be failing, because theyre interdependent. Developers need to reason about the system architecture, form hypotheses, and follow the chain of components until they have located the one that is the culprit. Otto focuses on application development and security.
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AWS Machine Learning Blog
DECEMBER 4, 2024
Generate accurate training data for SageMaker models – For model training, data scientists can use Tecton’s SDK within their SageMaker notebooks to retrieve historical features. The following graphic shows how Amazon Bedrock is incorporated to support generative AI capabilities in the fraud detection system architecture.
AWS Machine Learning Blog
JUNE 6, 2025
Organizations building or adopting generative AI use GPUs to run simulations, run inference (both for internal or external usage), build agentic workloads, and run data scientists’ experiments. The workloads range from ephemeral single-GPU experiments run by scientists to long multi-node continuous pre-training runs.
AWS Machine Learning Blog
FEBRUARY 13, 2025
To understand how this dynamic role-based functionality works under the hood, lets examine the following system architecture diagram. As shown in preceding architecture diagram, the system works as follows: The end-user logs in and is identified as either a manager or an employee.
ODSC - Open Data Science
JUNE 12, 2025
With a background as a founding ML engineer, data scientist, and curriculum designer, Chris brings deep technical knowledge and a passion for teaching. How the Summit Works Week 1: Foundations Dive into core agent systems — architecture, memory, planning, and frameworks.
AWS Machine Learning Blog
JANUARY 10, 2024
An ML model registered by a data scientist needs an approver to review and approve before it is used for an inference pipeline and in the next environment level (test, UAT, or production). When data scientists develop a model, they register it to the SageMaker Model Registry with the model status of PendingManualApproval.
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