Remove Metrics Remove Publishing Remove Testing
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Training and Testing Neural Networks on PyTorch using Ignite

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction With ignite, you can write loops to train the network in just a few lines, add standard metrics calculation out of the box, save the model, etc. The post Training and Testing Neural Networks on PyTorch using Ignite appeared first on Analytics Vidhya.

Testing 356
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Deploying ML Models Using Kubernetes

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. The Model development process undergoes multiple iterations and finally, a model which has acceptable performance metrics on test data is taken to the production […].

Modeling 346
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Top 18 Social Media KPIs & Metrics You Should Use For A Complete SM Strategy

datapine

Here, we’ll examine 18 essential KPIs for social media, explore the dynamics and demonstrate the importance of social metrics in the modern business age with the help of a KPI software , and, finally, wrapping up with tips on how to set KPIs and make the most of your social platforms. Let’s get going. What Are Social Media KPIs?

Metrics 219
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You Can’t Regulate What You Don’t Understand

O'Reilly on Data

Most notably, The Future of Life Institute published an open letter calling for an immediate pause in advanced AI research , asking: “Should we let machines flood our information channels with propaganda and untruth? Today, we have dozens of organizations that publish AI principles, but they provide little detailed guidance.

Metrics 359
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. The data quality analysis metrics of complete and accurate data are imperative to this step. Table of Contents. 2) Why Do You Need DQM?

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Start DataOps Today with ‘Lean DataOps’

DataKitchen

The best way to ensure error-free execution of data production is through automated testing and monitoring. The DataKitchen Platform enables data teams to integrate testing and observability into data pipeline orchestrations. Automated tests work 24×7 to ensure that the results of each processing stage are accurate and correct.

Testing 246
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Do You Need a DataOps Dojo?

DataKitchen

Centralizing analytics helps the organization standardize enterprise-wide measurements and metrics. With a standard metric supported by a centralized technical team, the organization maintains consistency in analytics. A centralized team can publish a set of software services that support the rollout of Agile/DataOps.

Metrics 243