The Unofficial Google Data Science Blog

OCTOBER 7, 2015

by HENNING HOHNHOLD, DEIRDRE O'BRIEN, and DIANE TANG In this post we discuss the challenges in measuring and modeling the long-term effect of ads on user behavior. We describe experiment designs which have proven effective for us and discuss the subtleties of trying to generalize the results via modeling.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

Domino Data Lab

AUGUST 22, 2019

The excerpt covers how to create word vectors and utilize them as an input into a deep learning model. While the field of computational linguistics, or Natural Language Processing (NLP), has been around for decades, the increased interest in and use of deep learning models has also propelled applications of NLP forward within industry.

Deep Learning 111

Deep Learning Modeling Metrics Testing 111

Ontotext

DECEMBER 30, 2022

9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. In 2008, we received a small round of funding and focused on bringing this technology to the market. However, developing these models from scratch for each and every solution can be slow, expensive and risky.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

Ontotext

DECEMBER 30, 2022

9 years of research, prototyping and experimentation went into developing enterprise ready Semantic Technology products. In 2008, we received a small round of funding and focused on bringing this technology to the market.

Enterprise 52

Enterprise Sales Cost-Benefit Marketing 52

CIO Business Intelligence

JUNE 27, 2022

Sentry was started as an open source project by David Cramer in 2008 to provide monitoring services for application developers. David Cramer: I love the open source community so I would build a lot of things in open source to interact with my peers. million developers today. How did that happen?

Software 113

Software Experimentation Testing Marketing 113

Data Science and Beyond

JULY 22, 2018

Kaggle was only about predictive modelling competitions back then, and so I believed that data science is about using machine learning to build models and deploy them as part of various applications. It is now much easier to deploy machine learning models, even without a deep understanding of how they work.

Data Science 79

Data Science Machine Learning Statistics Predictive Modeling 79

O'Reilly on Data

JULY 25, 2023

I’m a professor who is interested in how we can use LLMs (Large Language Models) to teach programming. And if I switch tabs to view a paper from 2008, then a song from 2008 could start up. graduate in Human-Computer Interaction and now a senior UX (user experience) designer at a top design firm.

Consulting 246

Consulting Interactive Software IT 246