O'Reilly on Data

JUNE 18, 2019

These data sets are often siloed, incomplete, and extremely sparse. Moreover, the domain knowledge, which often is not encoded in the data (nor fully documented), is an integral part of this data (see this article from Forbes). See this article on data integration status for details.

Machine Learning 259

Machine Learning Data Quality Statistics Modeling 259

Ontotext

DECEMBER 15, 2023

It includes only ML papers and related entities; this SPARQL query shows some statistics: papers tasks models datasets methods evaluations repos 376557 4267 24598 8322 2101 52519 153476 We can start with these repositories (most of them are on Github) and get all their topics. We use Categories as a way of finding relevant articles.

Machine Learning 69

Machine Learning Interactive Deep Learning Statistics 69

O'Reilly on Data

JULY 28, 2020

In this article, we turn our attention to the process itself: how do you bring a product to market? Products based on deep learning can be difficult (or even impossible) to develop; it’s a classic “high return versus high risk” situation, in which it is inherently difficult to calculate return on investment.

Marketing 362

Marketing Experimentation Metrics Testing 362

Sisense

APRIL 10, 2020

R is a tool built by statisticians mainly for mathematics, statistics, research, and data analysis. These visualizations are useful for helping people visualize and understand trends , outliers, and patterns in data. We’ll actually do this later in this article. R: Analytics powerhouse. R libraries.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smart Data Collective

MAY 8, 2022

Brands are closely working to solve this as they dive deep into the world of big data analytics. Well, don’t go anywhere because, in this article, we will show you how you can use big data analytics combined with AI to achieve the best performance possible. What is the relationship between big data analytics and AI?

Big Data 106

Big Data Data Analytics Analytics Cost-Benefit 106

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. There won’t be any need for them.

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

Domino Data Lab

JULY 22, 2019

He was saying this doesn’t belong just in statistics. He also really informed a lot of the early thinking about data visualization. It involved a lot of interesting work on something new that was data management. To some extent, academia still struggles a lot with how to stick data science into some sort of discipline.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109