SynapseML
azure-kusto-spark
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| SynapseML | azure-kusto-spark | |
|---|---|---|
| 18 | 1 | |
| 4,964 | 74 | |
| 0.5% | - | |
| 8.9 | 6.8 | |
| 2 days ago | about 1 month ago | |
| Scala | Scala | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
SynapseML
- FLaNK Stack Weekly for 12 September 2023
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Microsoft announces new tool for applying ChatGPT and GPT-4 at massive scales
Release Notes: https://github.com/microsoft/SynapseML/releases/tag/v0.11.0
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Data science in Scala
b) There are libraries around e.g. Microsoft SynapseML, LinkedIn Photon ML
- [N] Microsoft Announces New Integrations with OpenAI and MLFlow
- [N] Microsoft Releases new Integrations with OpenAI and MLflow as part of SynapseML
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[P] Microsoft releases SynapseML v0.9.5 with support for speech synthesis, anomaly detection, and geospatial analytics on large-scale data
Link to Release Notes: https://github.com/microsoft/SynapseML/releases/tag/v0.9.5
- Microsoft releases SynapseML v0.9.5 for distributed geospatial analytics, speech synthesis, and anomaly detection in PySpark.
- [P] SynapseML v0.9.5 announces support for geospatial analytics, speech synthesis, and anomaly detection on large-scale datasets
- Microsoft releases SynapseML v0.9.5 with support for speech synthesis, anomaly detection, and geospatial analytics on Apache Spark
azure-kusto-spark
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Getting started with Azure Data Explorer and Azure Synapse Analytics for Big Data processing
Azure Data Explorer is a fully managed data analytics service that can handle large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more. Azure Data Explorer makes it simple to ingest this data and enables you to do complex ad hoc queries on the data in seconds. It scales quickly to terabytes of data, in minutes, allowing rapid iterations of data exploration to discover relevant insights. It is already integrated with Apache Spark work via the Data Source and Data Sink Connector and is used to power solutions for near real-time data processing, data archiving, machine learning etc.
What are some alternatives?
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
isolation-forest - A Spark/Scala implementation of the isolation forest unsupervised outlier detection algorithm.
synapse-azure-data-explorer-101 - Getting started with Azure Synapse and Azure Data Explorer
kusto-queries - example queries for learning the kusto language
Breeze - Breeze is a numerical processing library for Scala.
frameless - Expressive types for Spark.
Tensorflow_scala - TensorFlow API for the Scala Programming Language
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
cobrix - A COBOL parser and Mainframe/EBCDIC data source for Apache Spark
Smile - Statistical Machine Intelligence & Learning Engine