Remove tag visual-modeling
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Dynatrace extends contextual analytics and AIOps for open observability

Dynatrace

Relying solely on traditional analysis methods like tagging and data correlation to answer such questions is inadequate when an IT landscape isn’t properly represented in a data model or when the cause-and-effect chain of services remains unclear.

Analytics 246
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Detecting Speech and Music in Audio Content

The Netflix TechBlog

Iroro Orife , Chih-Wei Wu and Yun-Ning (Amy) Hung Introduction When you enjoy the latest season of Stranger Things or Casa de Papel (Money Heist) , have you ever wondered about the secrets to fantastic story-telling, besides the stunning visual presentation? surround format at 48 kHz sampling rate.

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Open-Sourcing a Monitoring GUI for Metaflow

The Netflix TechBlog

The GUI can be extended with plugins, allowing the community to build integrations to other systems, custom visualizations, and embed upcoming features of Metaflow directly into its views. We also had no need to build a model-monitoring GUI yet, which is a wholly separate problem domain. all using their favorite IDEs and terminals.

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Dynatrace supports the newly released AWS Lambda Response Streaming

Dynatrace

In traditional request-response models, the response needs to be fully generated and buffered before it is returned to the client. Additionally, Dynatrace auto-discovers an environment and visualizes all its dependencies, so it can determine precisely how problems evolve and how they affect the user experience.

Lambda 216
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 4 Most Common Myths Around Test Automation

Testsigma

They include: Modeling application Test data generation Developing framework / reusable libraries Work towards CI-CD-CT CI = Continuous integration CD = Continuous delivery/deployment CT = Continuous testing Documenting automation / Preparing readme documents. lt allows anyone to create software, visually, without writing code”.

Testing 95
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Using JSONB in PostgreSQL: How to Effectively Store & Index JSON Data in PostgreSQL

Scalegrid

If you store each of the keys as columns, it will result in frequent DML operations – this can be difficult when your data set is large - for example, event tracking, analytics, tags, etc. It will result in a sequential scan: demo=# select * from books where data->'tags' ?

Storage 321
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Supporting content decision makers with machine learning

The Netflix TechBlog

In this post we explore how machine learning and statistical modeling can aid creative decision makers in tackling these questions at a global scale. Our approach is rooted in transfer learning , whereby performance on a target task is improved by leveraging model parameters learned on a separate but related source task.