Difference between revisions of "Cloudera"
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
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| − | [ | + | [https://www.youtube.com/results?search_query=Cloudera+Oryx+artificial+intelligence+deep+learning Youtube search...] |
| − | [ | + | [https://www.google.com/search?q=Cloudera+Oryx+deep+machine+learning+ML+artificial+intelligence ...Google search] |
* [[Libraries & Frameworks]] | * [[Libraries & Frameworks]] | ||
| − | * [ | + | * [https://github.com/cloudera/oryx Oryx | GitHub] |
| − | * [ | + | * [https://www.infoworld.com/article/2607749/hadoop/how-cloudera-plans-to-stand-out-from-the-hadoop-herd.html How Cloudera plans to stand out from the Hadoop herd | Serdar Yegulalp] |
| − | uses Spark and the Kafka stream processing framework to run machine learning models on real-time data. Oryx provides a way to build projects that require decisions in the moment, like recommendation engines or live anomaly detection, that are informed by both new and historical data. | + | uses [https://spark.apache.org/ Spark] and the [https://www.learningjournal.guru/article/kafka/kafka-enterprise-architecture/ Kafka] stream processing framework to run machine learning models on real-time data. Oryx provides a way to build projects that require decisions in the moment, like recommendation engines or live anomaly detection, that are informed by both new and historical data. |
<youtube>F8YVRzCdxcw</youtube> | <youtube>F8YVRzCdxcw</youtube> | ||
| + | <youtube>CoNX_mbFLZc</youtube> | ||
Latest revision as of 05:34, 28 March 2023
Youtube search... ...Google search
- Libraries & Frameworks
- Oryx | GitHub
- How Cloudera plans to stand out from the Hadoop herd | Serdar Yegulalp
uses Spark and the Kafka stream processing framework to run machine learning models on real-time data. Oryx provides a way to build projects that require decisions in the moment, like recommendation engines or live anomaly detection, that are informed by both new and historical data.
