Scalable End-to-End ML Platforms: from AutoML to Self-serve

no code implementations • 27 Feb 2023 • Igor L. Markov, Pavlos A. Apostolopoulos, Mia R. Garrard, Tanya Qie, Yin Huang, Tanvi Gupta, Anika Li, Cesar Cardoso, George Han, Ryan Maghsoudian, Norm Zhou

ML platforms help enable intelligent data-driven applications and maintain them with limited engineering effort.

AutoML

Looper: An end-to-end ML platform for product decisions

no code implementations • 14 Oct 2021 • Igor L. Markov, Hanson Wang, Nitya Kasturi, Shaun Singh, Sze Wai Yuen, Mia Garrard, Sarah Tran, Yin Huang, Zehui Wang, Igor Glotov, Tanvi Gupta, Boshuang Huang, Peng Chen, Xiaowen Xie, Michael Belkin, Sal Uryasev, Sam Howie, Eytan Bakshy, Norm Zhou

Modern software systems and products increasingly rely on machine learning models to make data-driven decisions based on interactions with users, infrastructure and other systems.

Decision Making

Tumor Classification and Segmentation of MR Brain Images

no code implementations • 31 Oct 2017 • Tanvi Gupta, Pranay Manocha, Tapan K. Gandhi, RK Gupta, BK Panigrahi

The diagnosis and segmentation of tumors using any medical diagnostic tool can be challenging due to the varying nature of this pathology.

Classification General Classification +2

Automated Tumor Segmentation and Brain Mapping for the Tumor Area

no code implementations • 28 Oct 2017 • Pranay Manocha, Snehal Bhasme, Tanvi Gupta, BK Panigrahi, Tapan K. Gandhi

Magnetic Resonance Imaging (MRI) is an important diagnostic tool for precise detection of various pathologies.

Brain Tumor Segmentation Clustering +2