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5 Ways Local SEO Companies Are Optimizing Their Models With Big Data

Smart Data Collective

Large companies around the world are investing in big data. Big data has been especially important for optimizing their marketing campaigns. Local marketing agencies have discovered that SEO is more dependent on big data than ever. How local companies rely on big data to drive organic search engine traffic.

Big Data 111
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Proposals for model vulnerability and security

O'Reilly on Data

Apply fair and private models, white-hat and forensic model debugging, and common sense to protect machine learning models from malicious actors. Like many others, I’ve known for some time that machine learning models themselves could pose security risks.

Modeling 219
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Becoming a machine learning company means investing in foundational technologies

O'Reilly on Data

Companies successfully adopt machine learning either by building on existing data products and services, or by modernizing existing models and algorithms. In this post, I share slides and notes from a keynote I gave at the Strata Data Conference in London earlier this year. A typical data pipeline for machine learning.

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Artificial intelligence and machine learning adoption in European enterprise

O'Reilly on Data

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. You can find full results from the survey in the free report “Evolving Data Infrastructure”.). Deep Learning.

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Introducing the 2019 Data Heroes – EMEA!

Cloudera

The Data Heroes initiative is one of the ways that we recognize customers who achieve outstanding results with Cloudera technologies. The Data Visionary, Data Scientist, Data Architect, and HCC Community Champion awards are given out to organizations transforming their businesses through Big Data.

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The DataOps Vendor Landscape, 2021

DataKitchen

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Testing and Data Observability.

Testing 300
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Data Analytics Contributes to the Abrupt Rise of Clean Energy Investment

Smart Data Collective

Big data technology has become a major disrupting factor in the energy industry. Many energy conglomerates have started embracing data analytics to expand their markets, respond to new trends, streamline operations and bolster efficiency. The clean energy sector has not been untouched by the big data revolution.