Return to page Blog

Filter By:

5 results Category: Year:
H2O Releases and
by Marek Novotny, Wendy Wong | June 23, 2023 GBM , GLM , H2O Release , H2O-3 , XGBoost

Our new major releases of H2O are packed with new features and fixes! Some of the major highlights of these releases are the new Decision Tree algorithm, the added ability to grid over Infogram, an upgrade to the version of XGBoost and an improvement to its speed, the completion of the maximum likelihood dispersion parameter and its expan...

Read more
The Benefits of Budget Allocation with AI-driven Marketing Mix Models
by Michael Proksch | September 17, 2020 AutoML , Business , Customers , GBM , GLM , Machine Learning , Solutions

Excerpt of the white paper: “The Latest in AI Technologies Reinvent Media and Marketing Analytics @ Allergan” Authors: Akhil Sood, Associate Director @ Marketing Sciences, Allergan Dr. Michael Proksch, Senior Director @ Vijay Raghavan, Associate Vice President @ Marketing Sciences, AllerganIntroductionThe call for accountability in...

Read more
From GLM to GBM – Part 2

How an Economics Nobel Prize could revolutionize insurance and lending Part 2: The Business Value of a Better ModelIntroductionIn Part 1 , we proposed better revenue and managing regulatory requirements with machine learning (ML). We made the first part of the argument by showing how gradient boosting machines (GBM), a type of ML, can mat...

Read more
From GLM to GBM - Part 1

How an Economics Nobel Prize could revolutionize insurance and lending Part 1: A New Solution to an Old ProblemIntroductionInsurance and credit lending are highly regulated industries that have relied heavily on mathematical modeling for decades. In order to provide explainable results for their models, data scientists and statisticians i...

Read more Releases H2O4GPU, the Fastest Collection of GPU Algorithms on the Market, to Expedite Machine Learning in Python
by Team | September 26, 2017 GBM , GLM , GPU , k-Means

H2O4GPU is an open-source collection of GPU solvers created by It builds on the easy-to-use scikit-learn Python API and its well-tested CPU-based algorithms. It can be used as a drop-in replacement for scikit-learn with support for GPUs on selected (and ever-growing) algorithms. H2O4GPU inherits all the existing scikit-learn algor...

Read more

No results found. 
Please modify your search.