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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

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.

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Sentry’s David Cramer on bootstrapping a unicorn

CIO Business Intelligence

Sentry was started as an open source project by David Cramer in 2008 to provide monitoring services for application developers. A lot of the current approaches feel very experimental and are tough to see as maintainable, so there’s certainly still room for growth here. million developers today.

Software 104
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Real-Real-World Programming with ChatGPT

O'Reilly on Data

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. Setting the Stage: Who Am I and What Am I Trying to Build? This choice also inspired me to call my project Swift Papers.

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Ontotext Expands To Help More Enterprises Turn Their Data into Competitive Advantage

Ontotext

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.

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Ontotext 2023: Accelerating Our Growth to Enable Business Success for Enterprises

Ontotext

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.

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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

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.

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Defining data science in 2018

Data Science and Beyond

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.