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MLOps and the evolution of data science

IBM Big Data Hub

Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. These insights can help drive decisions in business, and advance the design and testing of applications.

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Magnificent Mobile Website And App Analytics: Reports, Metrics, How-to!

Occam's Razor

They will need two different implementations, it is quite likely that you will end up with two sets of metrics (more people focused for mobile apps, more visit focused for sites). In this post we will look mobile sites first, both data collection and analysis, and then mobile applications. And again, a custom set of metrics.

Metrics 141
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It's Not The Ink, It's The Think: 6 Effective Data Visualization Strategies

Occam's Razor

Ten years, and the 944,357 words, are proof that I love purposeful data, collecting it, pouring smart strategies into analyzing it, and using the insights identified to transform organizations. There is only one simple message above, and just two metrics that matter. It can be any of the numerous brand metrics avilable to us.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. After forming the X and y variables, we split the data into training and test sets. 2015) for additional details. random_state=seed) y_train.value_counts().

Modeling 139
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Crushing It With Competitive Intelligence Analysis: Best Metrics, Reports

Occam's Razor

How is competitive intelligence data collected? Competitive intelligence data will never match your site's analytics tool. Traffic Trends Key Metrics Analysis. Onsite Behavior Key Metrics Analysis. Content Consumption Competitive Analysis. + #OMG Mobile, Where's Mobile Data! CI data collection.

Metrics 155