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Illuminating the black box: why CIOs should consider publishing an annual IT report

CIO Business Intelligence

One vehicle might be an annual report, one similar to those that have been published for years by public companies—10ks and 10qs and all those other filings by which stakeholders judge a company’s performance, posture, and potential. Such a report has a legacy already, if only a short one. Remind yourself of these principles as you work.

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The history of ESG: A journey towards sustainable investing

IBM Big Data Hub

It refers to a set of metrics used to measure an organization’s environmental and social impact and has become increasingly important in investment decision-making over the years. In response, asset managers began to develop ESG strategies and metrics to measure the environmental and social impact of their investments.

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Drug Discovery Needs AI To Discover More Treatments

Smart Data Collective

In a report on the failure rates of drug discovery efforts between 2013 and 2015, Richard K. An open and impartial AI model should be able to inject a measure of transparency into this process along with the obvious efficiency advantages. Unfortunately, a substantial number of clinical trials fails in these two Phases.

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Insight Boston Alumni: Where are they now?

Insight

Insight Boston began its journey in 2015, with the first and only fellowship program dedicated to a career in Health Data Science. Jerry Chen was a Health Data Fellow in 2017 and joined Wayfair as a Senior Data Scientist on their Marketing team; he now manages the Data Science Measurement team.

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Remove Your Rose Tinted Glasses: Data Visualizations Designed to Mislead

datapine

See these graphs originally published by Cogent Legal. In the above example from the 2015 Congressional Hearing based on Planned Parenthood, we can see clear-cut results showing a rise in abortions and a drop in cancer-related health services.

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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. Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning.

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Fitting Support Vector Machines via Quadratic Programming

Domino Data Lab

Support Vector Machines (SVMs) are supervised learning models with a wide range of applications in text classification (Joachims, 1998), image recognition (Decoste and Schölkopf, 2002), image segmentation (Barghout, 2015), anomaly detection (Schölkopf et al., Springer International Publishing. 1999) and more. References. Barghout, L.