Based on our record, Apache Spark seems to be a lot more popular than Azure Machine Learning Studio. While we know about 57 links to Apache Spark, we've tracked only 2 mentions of Azure Machine Learning Studio. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Machine Learning studio https://studio.azureml.net/ but this will be discontinued in Dec 01,2021 :(. Source: over 2 years ago
Advanced analytics, predictive modeling: You can't go passed learning R or Python if you're that way inclined.. however, if you're a GUI monkey like me, I have had a fair amount of success using https://studio.azureml.net/ it's free at base level :). Source: almost 3 years ago
In contrast, Databricks maintains internal forks of Spark, Delta Lake, and Unity Catalog, using the same names for both the open-source versions and the features specific to the Databricks platform. While they do provide separate documentation, online discussions often reflect confusion about how to use features in the open-source versions that only exist on the Databricks platform. This creates a "muddying of the... - Source: dev.to / about 11 hours ago
Recently I had to revisit the "JVM languages universe" again. Yes, language(s), plural! Java isn't the only language that uses the JVM. I previously used Scala, which is a JVM language, to use Apache Spark for Data Engineering workloads, but this is for another post 😉. - Source: dev.to / 3 months ago
Consume data into third party software (then let Open Search or Apache Spark or Apache Pinot) for analysis/datascience, GIS systems (so you can put reports on a map) or any ticket management system. - Source: dev.to / 5 months ago
Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 6 months ago
Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 6 months ago
IBM Watson Studio - Learn more about Watson Studio. Increase productivity by giving your team a single environment to work with the best of open source and IBM software, to build and deploy an AI solution.
Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
Hadoop - Open-source software for reliable, scalable, distributed computing