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14 essential book recommendations by and for IT leaders

CIO Business Intelligence

This step-by-step guide to designing a high-functioning organization helps you understand four team types and interaction patterns and helps you to type and build it. “It By defining team types, their fundamental interactions, and the science behind them, you learn how to better model your organizations according to these definitions.

IT 114
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PODCAST: COVID19 | Redefining Digital Enterprises – Episode 6: The Impact of COVID-19 on Supply Chain Management

bridgei2i

You know the markets shake and the accompanying Swine Flu epidemic of 2015 and 2016, the Japanese tsunami and the Thailand floods in 2011 that shook up the high-tech value chain quite a bit, the great financial crisis and the accompanying H1N1 outbreak in 2008-2009, MERS and SARS before that in 2003.

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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., Granular computing and decision-making: Interactive and iterative approaches (pp.

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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

Let's listen in as Alistair discusses the lean analytics model… The Lean Analytics Cycle is a simple, four-step process that shows you how to improve a part of your business. Another way to find the metric you want to change is to look at your business model. The business model also tells you what the metric should be.

Metrics 156
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PODCAST: COVID19 | Redefining Digital Enterprises – Episode 14: Strategic priorities for Sales leaders through the crisis

bridgei2i

You know that, when we went through the last business downturn, 2008 in 2009, funny thing happened in 2010 turnover went up dramatically in sales and because companies started hiring again. There’s also going to be challenges and we have no idea how to model this. And so you’ve got to ask yourself a question.

Sales 98
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Adding Common Sense to Machine Learning with TensorFlow Lattice

The Unofficial Google Data Science Blog

by TAMAN NARAYAN & SEN ZHAO A data scientist is often in possession of domain knowledge which she cannot easily apply to the structure of the model. On the one hand, basic statistical models (e.g. On the other hand, sophisticated machine learning models are flexible in their form but not easy to control.

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Exploring US Real Estate Values with Python

Domino Data Lab

This post covers data exploration using machine learning and interactive plotting. Models are at the heart of data science. Data exploration is vital to model development and is particularly important at the start of any data science project. Interactive Data Visualization in Python. Introduction. fill=True,).: