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. Data Engineer. This is the best time ever to pursue this career track.

Data Science 144

Data Science Data Scientist Machine Learning Machine Learning 144

Flipboard

APRIL 23, 2025

This endpoint based architecture provides decoupling between the other processing, allowing independent scaling, versioning, and maintenance of each component. The decoupled nature of the endpoints also provides flexibility to update or replace individual models without impacting the broader system architecture.

AWS 109

AWS ML ML AI 109

AWS Machine Learning Blog

JANUARY 10, 2024

Specialist Data Engineering at Merck, and Prabakaran Mathaiyan, Sr. ML Engineer at Tiger Analytics. He has extensive experience in enterprise systems architecture and operations across several industries – particularly in Health Care and Life Science. This post is co-written with Jayadeep Pabbisetty, Sr.

ML 129

ML ML AWS Machine Learning 129

AWS Machine Learning Blog

MAY 23, 2023

With a comprehensive suite of technical artifacts, including infrastructure as code (IaC) scripts, data processing workflows, service integration code, and pipeline configuration templates, PwC’s MLOps accelerator simplifies the process of developing and operating production-class prediction systems.

Machine Learning 101

Machine Learning Machine Learning AWS ML 101

Pickl AI

DECEMBER 4, 2023

First, I will answer the fundamental question ‘What is Data Intelligence?’. What is Data Intelligence in Data Science? Wondering what is Data Intelligence in Data Science? In simple terms, Data Intelligence is like having a super-smart assistant for big companies. So, let’s get started.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 52

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.

AWS 116

AWS AI AI Machine Learning 116