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XAI: Accuracy vs Interpretability for Credit-Related Models

Analytics Vidhya

Introduction The global financial crisis of 2007 has had a long-lasting effect on the economies of many countries. The post XAI: Accuracy vs Interpretability for Credit-Related Models appeared first on Analytics Vidhya. The post XAI: Accuracy vs Interpretability for Credit-Related Models appeared first on Analytics Vidhya.

Modeling 395
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MongoDB Enhances Developer Data Platform

David Menninger's Analyst Perspectives

MongoDB was founded in 2007 and has established itself as one of the most prominent NoSQL database providers with its document-oriented database and associated cloud services. Although well-established as a developer data platform provider, MongoDB continues to add product experience functionality to compete with more established rivals.

Data Lake 130
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

This thought was in my mind as I was reading Lean Analytics a new book by my friend Alistair Croll and his collaborator Benjamin Yoskovitz. In this post, we’ll look at each of the four steps in the Lean Analytics Cycle in more detail. Let’s look at some case studies that will really help to drive the Lean Analytics Cycle home.

Metrics 157
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The Week The Modern Analytics and BI Market Changed Forever

Rita Sallam

This week, Cloud megavendors Google and Salesforce bought modern analytics and BI vendors Looker and Tableau, respectively, to complement their cloud data management and application stacks and to drive data and compute-intensive analytics use cases to their respective clouds. There are differences in the two acquisitions, however.

Marketing 110
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Transforming FSI in ASEAN with Cloud Analytics

CIO Business Intelligence

auxmoney began as a peer-to-peer lender in 2007, with the mission of improving access to credit and promoting financial inclusion. Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. The Challenges in Scaling Analytics .

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Telecom Network Analytics: Transformation, Innovation, Automation

Cloudera

One of the most substantial big data workloads over the past fifteen years has been in the domain of telecom network analytics. The Dawn of Telco Big Data: 2007-2012. The initial stage of the third phase of Telecom Data Analytics has often been mischaracterized as merely a shift to cloud. Where does it stand today?

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Unlock the power of optimization in Amazon Redshift Serverless

AWS Big Data

Most analytical workloads operate on millions or even billions of rows and generate aggregations and complex calculations. About the Authors Ricardo Serafim is a Senior Analytics Specialist Solutions Architect at AWS. He has been helping companies with Data Warehouse solutions since 2007.