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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Apache Spark with minimal hand-tuning
| Date | Stars |
|---|---|
| 2026-07-31 | 2279 |
| 2026-08-03 | 2279 |
| 2026-08-06 | 2278 |
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# TransmogrifAI [](https://search.maven.org/search?q=g:com.salesforce.transmogrifai) [](https://www.javadoc.io/doc/com.salesforce.transmogrifai/transmogrifai-core_2.11/0.7.0) [](https://spark.apache.org/downloads.html) [](https://www.scala-lang.org/download/2.11.12.html) [](./LICENSE) [](https://gitter.im/salesforce/TransmogrifAI?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [](https://travis-ci.com/salesforce/TransmogrifAI) [](https://circleci.com/gh/salesforce/TransmogrifAI) [](https://docs.transmogrif.ai/en/stable/?badge=stable) [](https://bestpractices.coreinfrastructure.org/projects/2557) [](https://www.codefactor.io/repository/github/salesforce/transmogrifai) TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library written in Scala that runs on top of Apache Spark. It was developed with a focus on accelerating machine learning developer productivity through machine learning automation, and an API that enforces compile-time type-safety, modularity, and reuse. _Through automation, it achieves accuracies close to hand-tuned models with almost 100x reduction in time._ Use TransmogrifAI if you need a machine learning library to: * Build production ready machine learning applications in hours, not months * Build machine learning models without getting a Ph.D. in machine learning * Build modular, reusable, strongly typed machine learning workflows To understand the motivation behind TransmogrifAI check out these: - [Open Sourcing TransmogrifAI: Automated Machine Learning for Structured Data](https://engineering.salesforce.com/open-sourcing-transmogrifai-4e5d0e098da2), a blog post by [@snabar](https://github.com/snabar) - [Meet TransmogrifAI, Open Source AutoML That Powers Einstein Predictions](https://www.youtube.com/watch?v=93vsqjfGPCw&feature=youtu.be&t=2800), a talk by [@tovbinm](https://github.com/tovbinm) - [Low Touch Machine Learning](https://www.youtube.com/watch?v=PKTvo9X9Sjg), a talk by [@leahmcguire](https://github.com/leahmcguire) Skip to [Quick Start and Documentation](#quick-start-and-documentation). ## Predicting Titanic Survivors with TransmogrifAI The Titanic dataset is an often-cited dataset in the machine learning community. The goal is to build a machine learnt model that will predict survivors from the Titanic passenger manifest. Here is how you would build the model using TransmogrifAI: ```scala import com.salesforce.op._ import com.salesforce.op.readers._ import com.salesforce.op.features._ import com.salesforce.op.features.types._ import com.salesforce.op.stages.impl.classification._ import org.apache.spark.SparkConf import org.apache.spark.sql.SparkSession implicit val spark = SparkSession.builder.config(new SparkConf()).getOrCreate() import spark.implicits._ // Read Titanic data as a DataFrame val passengersData = DataReaders.Simple.csvCase[Passenger](path = pathToData).readDataset().toDF() // Extract response and predictor Features val (
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:7137da43f3de7e48, llm:Topics and description: 'AutoML library', 'automated-machine-learning', 'automl', 'feature-engineering', 'pipelines', 'spark', 'sparkml', 'structured-data' and readme: 'AutoML library ... runs on top of Apache Spark'
matched fp:7137da43f3de7e48, llm:Topics and description: 'AutoML library', 'automated-machine-learning', 'automl', 'feature-engineering', 'pipelines', 'spark', 'sparkml', 'structured-data' and readme: 'AutoML library ... runs on top of Apache Spark'
matched fp:7137da43f3de7e48, llm:Topics and description: 'AutoML library', 'automated-machine-learning', 'automl', 'feature-engineering', 'pipelines', 'spark', 'sparkml', 'structured-data' and readme: 'AutoML library ... runs on top of Apache Spark'