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Towards optimal experimentation in online systems

The Unofficial Google Data Science Blog

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

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Enterprise Data Science Workflows with AMPs and Streamlit

Cloudera

Here in the virtual Fast Forward Lab at Cloudera , we do a lot of experimentation to support our applied machine learning research, and Cloudera Machine Learning product development. Only through hands-on experimentation can we discern truly useful new algorithmic capabilities from hype. Not all of them require a unique front-end.

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Belcorp reimagines R&D with AI

CIO Business Intelligence

Belcorp operates under a direct sales model in 14 countries. As Belcorp considered the difficulties it faced, the R&D division noted it could significantly expedite time-to-market and increase productivity in its product development process if it could shorten the timeframes of the experimental and testing phases in the R&D labs.

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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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Smarter Survey Results and Impact: Abandon the Asker-Puker Model!

Occam's Razor

Bonus #2: The Askers-Pukers Business Model. Hypothesis development and design of experimentation. Econsultancy/Lynchpin provides this description in the report: "There were 960 respondents to our research request, which took the form of a global online survey fielded in May and June 2016. Bottom-line. Truly listen.

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AWS: Moving Beyond Infrastructure to Monetize its Ecosystem

Hurwitz & Associates

In 2016 Amazon announced that the Amazon AI platform as a way to bring AI tools to its developer community. And I have to admit the level of innovation and experimentation is breathtaking. Machine Learning and AI take center stage. It also has an advantage of being able to attract legacy vendors that want to play in the new world.

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HPE Looks to Edge-to-Cloud Strategy for Growth in 2018/2019

Hurwitz & Associates

HPE then shed its software business, selling it to MicroFocus in 2016, and its EDS services business, selling it to CSC that same year. The $4 billion investment will be used for R&D, product development, technical services and the development of new consumption models for Edge and cloud. Consumption models are changing.