Remove tag machine-learning
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Machine Learning for Fraud Detection in Streaming Services

The Netflix TechBlog

Data analysis and machine learning techniques are great candidates to help secure large-scale streaming platforms. These models learn the distributions of benign samples and leverage that knowledge for identifying anomalous samples at the inference time.

C++ 312
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New Series: Creating Media with Machine Learning

The Netflix TechBlog

By Vi Iyengar , Keila Fong , Hossein Taghavi , Andy Yao , Kelli Griggs , Boris Chen , Cristina Segalin , Apurva Kansara , Grace Tang , Billur Engin , Amir Ziai , James Ray , Jonathan Solorzano-Hamilton Welcome to the first post in our multi-part series on how Netflix is developing and using machine learning (ML) to help creators make better media?—?from

Media 239
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Dynatrace supports Amazon Linux 2023 as an AWS launch partner

Dynatrace

Saving your cloud operations and SRE teams hours of guesswork and manual tagging, the Davis AI engine analyzes billions of events in real time. Auto-detection starts monitoring new virtual machines as they are deployed. To learn more about Dynatrace and to start your free trial, visit the Dynatrace website.

AWS 281
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IT Operations: A Use Case in the 2023 Gartner Critical Capabilities for Application Performance Monitoring and Observability

Dynatrace

Teams get bogged down manually tagging data, reacting to alert storms, switching between disconnected dashboards, tediously trying to restore and correlate observability data from an archive, or interpreting incomplete data because of sampling or lack of retention. Want to learn more?

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Benchmark (YCSB) numbers for Redis, MongoDB, Couchbase2, Yugabyte and BangDB

High Scalability

This is guest post by Sachin Sinha who is passionate about data, analytics and machine learning at scale. Application example: photo tagging; add a tag is an update, but most operations are to read tags. Author & founder of BangDB. Workload B: Read mostly workload. This workload has a 95/5 reads/write mix.

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Enhanced root cause analysis using events

Dynatrace

For example, Dynatrace organizes entities into management zones and can tag them with important information, such as the owner and environment. Dynatrace Davis automatically discovers what’s machine knowable. What configuration changed is often machine knowable, but: Why was it changed? Tag your host with demo: cpu_stress.

DevOps 181
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Measuring the importance of data quality to causal AI success

Dynatrace

Another common impediment is manual data tagging and handling, an error-prone process that teams should minimize. Human involvement should be limited to verifying the features or attributes machine learning algorithms use to make predictions or decisions.