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Why Reinvent the Wheel? The Challenges of DIY Open Source Analytics Platforms

Cloudera

In their effort to reduce their technology spend, some organizations that leverage open source projects for advanced analytics often consider either building and maintaining their own runtime with the required data processing engines or retaining older, now obsolete, versions of legacy Cloudera runtimes (CDH or HDP).

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What Do CIOs Have To Know About Business Intelligence?

The Accidental Successful CIO

These BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps designed to provide users with detailed intelligence about the state of the business. The challenge that CIOs are facing is how best to make use of these new tools?

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Supporting Diverse ML Systems at Netflix

Netflix Tech

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

System 90
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What you need to know about product management for AI

O'Reilly Media - Ideas

We won’t go into the mathematics or engineering of modern machine learning here. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data.

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Netflix at AWS re:Invent 2019

Netflix Tech

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. Wednesday?—?December

AWS 40
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Netflix at AWS re:Invent 2019

Netflix Tech

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. Wednesday?—?December

AWS 40
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Interpreting predictive models with Skater: Unboxing model opacity

O'Reilly Media - Data

Data Scientist Cathy O’Neil has recently written an entire book filled with examples of poor interpretability as a dire warning of the potential social carnage from misunderstood models—e.g., There is also a trade off in balancing a model’s interpretability and its performance.