Cloudera

AUGUST 20, 2020

UOB used deep learning to improve detection of procurement fraud, thereby fighting financial crime. Acceptance that it will be an experiment — ML really requires a lot of experimentation, and often times you don’t know what’s going to be successful. So, the business has to accept and be willing to fail at it.

Enterprise 120

Enterprise Experimentation Uncertainty Deep Learning 120

IBM Big Data Hub

APRIL 18, 2024

While these large language model (LLM) technologies might seem like it sometimes, it’s important to understand that they are not the thinking machines promised by science fiction. Most experts categorize it as a powerful, but narrow AI model. A key trend is the adoption of multiple models in production.

Cost-Benefit 95

Cost-Benefit Modeling Manufacturing Interactive 95

Ontotext

NOVEMBER 6, 2019

GraphDB Workbench is the interface for Ontotext’s semantic graph database, which provides the core infrastructure including modelling agility, data integration, relationship exploration and cross-enterprise semantic data publishing and consumption. The Plugins. The RDFRank plugin is one of the most popular plugins for GraphDB.

Experimentation 45

Experimentation Deep Learning Software Modeling 45

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. This unified experience optimizes the process of developing and deploying ML models by streamlining workflows for increased efficiency.

Machine Learning 78

Machine Learning Manufacturing Cost-Benefit Deep Learning 78

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. Datatron — Automates deployment and monitoring of AI models.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Domino Data Lab

FEBRUARY 12, 2020

this post on the Ray project blog ?. for model serving (experimental), are implemented with Ray internally for its scalable, distributed computing and state management benefits, while providing a domain-specific API for the purposes they serve. Motivations for Ray: Training a Reinforcement Learning (RL) Model.

Experimentation 137

Experimentation Modeling Data Science Management 137

Domino Data Lab

MAY 8, 2019

Paco Nathan’s latest article features several emerging threads adjacent to model interpretability. I’ve been out themespotting and this month’s article features several emerging threads adjacent to the interpretability of machine learning models. Machine learning model interpretability. Introduction.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

CDW Research Hub

AUGUST 21, 2019

Some solutions require enough servers to start filling a rack in order to achieve the computer processing needed to create more powerful AI models. Equipped with IBM’s Deep Learning frameworks bundle, Watson Machine Learning Accelerator (WMLA), formerly called PowerAI, the solution is designed for use by 3-5 data scientists.

Strategy 45

Strategy Deep Learning Machine Learning Experimentation 45

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. Models trained in DataRobot can also be easily deployed to Azure Machine Learning, allowing users to host models easier in a secure way.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

Domino Data Lab

OCTOBER 14, 2020

We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield. For example, our models can show farmers how to increase their production while using less fertilizer.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Like this blog, it will be particularly relevant for those who are in digital analytics and digital marketing. Intro to Machine Learning. Machine Learning.

Marketing 136

Marketing Analytics Machine Learning Strategy 136