AWS Machine Learning Blog

APRIL 26, 2023

You may have gaps in skills and technologies, including operationalizing ML solutions, implementing ML services, and managing ML projects for rapid iterations. Ensuring data quality, governance, and security may slow down or stall ML projects. He has a background in software engineering and AI research.

ML 109

ML Machine Learning Data Science Data Drift 109

The MLOps Blog

NOVEMBER 14, 2023

Visualizing deep learning models can help us with several different objectives: Interpretability and explainability: The performance of deep learning models is, at times, staggering, even for seasoned data scientists and ML engineers. Data scientists and ML engineers: Creating and training deep learning models is no easy feat.

Deep Learning 111

Deep Learning Neural Network Convolutional Neural Networks Data Scientist 111

Snorkel AI

JUNE 9, 2023

Applying weak supervision and foundation models for computer vision Snorkel AI Machine Learning Research Scientist Ravi Teja Mullapudi discussed the latest advancements in computer vision, focusing on the use of weak supervision and foundation models.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

Snorkel AI

JUNE 9, 2023

Applying weak supervision and foundation models for computer vision Snorkel AI Machine Learning Research Scientist Ravi Teja Mullapudi discussed the latest advancements in computer vision, focusing on the use of weak supervision and foundation models.

Large Language Models 52

Large Language Models Data Scientist Machine Learning Computer Vision 52

The MLOps Blog

AUGUST 11, 2023

Getting a workflow ready which takes your data from its raw form to predictions while maintaining responsiveness and flexibility is the real deal. At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. Synchronous training What is synchronous training architecture?

ML 52

ML Machine Learning Data Ingestion Deep Learning 52