Ontotext

DECEMBER 1, 2023

Lance Paine, founder of Semantic Partners, took the ball from Sumit to talk about “why you’re not ready for knowledge graphs”. He outlined the challenges of working effectively with AI and machine learning, where knowledge graphs are a differentiator.

Metadata 78

Metadata Sales Machine Learning Consulting 78

Ontotext

MARCH 8, 2023

Several factors are driving the adoption of knowledge graphs. Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Domino Data Lab

JUNE 15, 2021

Now let’s implement a simple machine learning scoring function against our test data. custom machine learning algorithms), etc. This facilitates knowledge discovery, handover, and regulatory compliance, and allows the individual data scientists to focus on work that accelerates research and speeds model deployment.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Domino Data Lab

DECEMBER 4, 2020

The openness of the Domino Data Science platform allows us to use any language, tool, and framework while providing reproducibility, compute elasticity, knowledge discovery, and governance. In this tutorial, we demonstrated how to carry out a simple Non-Compartmental Analysis.

Metrics 59

Metrics Data Science Knowledge Discovery Measurement 59

The Unofficial Google Data Science Blog

NOVEMBER 4, 2015

by OMKAR MURALIDHARAN Many machine learning applications have some kind of regression at their core, so understanding large-scale regression systems is important. But most common machine learning methods don’t give posteriors, and many don’t have explicit probability models. For more on ad CTR estimation, refer to [2].

KDD 40

KDD Testing Machine Learning Measurement 40

Domino Data Lab

AUGUST 1, 2021

The interest in interpretation of machine learning has been rapidly accelerating in the last decade. This can be attributed to the popularity that machine learning algorithms, and more specifically deep learning, has been gaining in various domains. Conference on Knowledge Discovery and Data Mining, pp.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

Ontotext

AUGUST 31, 2023

Have you ever been in a conversation where someone mentioned a “knowledge graph,” only to realize that their description was completely different from what you had in mind? Imagine that you want to optimize your supply chain using machine learning. But what does it mean to ‘optimize the supply chain’?

Modeling 64

Modeling Knowledge Discovery Optimization Enterprise 64

CIO Business Intelligence

MARCH 26, 2025

The combination of AI and search enables new levels of enterprise intelligence, with technologies such as natural language processing (NLP), machine learning (ML)-based relevancy, vector/semantic search, and large language models (LLMs) helping organizations finally unlock the value of unanalyzed data. How did we get here?

Knowledge Discovery 84

Knowledge Discovery Cost-Benefit Enterprise Modeling 84

Ontotext

NOVEMBER 11, 2024

Given that many researchers say that between 75-85% of an organization’s knowledge is locked in static documents, tremendous value and wisdom are being missed. NLP pipelines benefit enormously, as sophisticated text analysis methods can be used when combining machine learning with knowledge graphs.

Metadata 52

Metadata Knowledge Discovery Data Integration Management 52