5 Key Considerations in Picking an AutoML Platform

Presented by

Vinod Iyengar, H2O.ai & Bojan Tunguz, H2O.ai

About this talk

AutoML platforms and solutions are quickly becoming the dominant way for every enterprise that is looking to implement and scale their ML and AI projects. As Forrester pointed out, these tools are trying to automate the end-to-end life cycle of developing and deploying predictive models — from data prep through feature engineering, model training, validation and deployment. This often involves evaluating numerous platforms and identifying the best fit for their organization. The decision process is based on multiple considerations, including accuracy, ease-of-use, performance, integration with existing tools, economics, competitive differentiation, solution maturity, risk tolerance, regulatory compliance considerations and more. Tune into this webinar to learn about the top 5 considerations in selecting an AutoML platform. Vinod will be joined by one of H2O.ai's Kaggle Grandmasters, Bojan Tunguz, for the discussion.

Related topics:

More from this channel

Upcoming talks (0)
On-demand talks (111)
Subscribers (19201)
H2O.ai is the maker of H2O, the world's best machine learning platform and Driverless AI, which automates machine learning. H2O is used by over 200,000 data scientists and more than 18,000 organizations globally. H2O Driverless AI does auto feature engineering and can achieve 40x speed-ups on GPUs.