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

Java library and command-line application for converting Apache Spark ML pipelines to PMML

SparkMLlibDeepLearn深度学习

spark 机器学习:利用jupyter工作来讲解算法原理并运行相关例子

Spark ML with pyspark

Because its never late to start taking notes and 'public' it...

This code is used to build & run a Docker container for performing predictions against a Spark ML Pipeline.

JPMML-SparkML plugin for converting LightGBM-Spark models to PMML

基于SparkML2.0进行的Kaggle、JData等比赛

:sparkle: 基于SparkMLLib实现的商品推荐功能，包括：基于用户的协同过滤，基于物品的协同过滤，基于ALS交替最小二乘的协同过滤。

A new stock trading and prediction model based on a MLP neural network utilizing technical analysis indicator values as features (using Apache Spark MLlib)

JPMML-SparkML plugin for converting XGBoost4J-Spark models to PMML

基于Spark+SparkMLlib+Debezium+Deequ打造的简单易用、超高性能大数据治理引擎。适用于批流一体的数据集成和数据分析，支持CDC实时数据采集、机器学习算法模型、数据质量校验、数据标注、敏感数据识别、数据建模、算法建模和OLAP数据分析

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Machine learning utilities for model conversion, serialization, loading etc

PMML scoring library for Spark as SparkML Transformer

Python PMML scoring library for PySpark as SparkML Transformer

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:sparkles: Spark ML implementation of SOM algorithm (Kohonen self-organizing map)

SparkMLlib智慧交通项目

Recommendation engine in Java. Based on an ALS algorithm (Apache Spark). Train a new model after N seconds.

We used deep learning models on SparkML to create a hybrid recommender system that leverages both content and collaborative data.

Simulation of job offers and CVs with real-time processing, classification, and analytics using Kafka, Ray, Spark, and Databricks. Includes a Flask-based recommendation system and Tableau visualizations.

A collection of “cookbook-style” scripts for simplifying data engineering and machine learning in Apache Spark.

Detailed notes and code to learn machine learning with Apache Spark.

Free High-Quality Financial Data in Azure

Helper functions for building complex Spark ML pipelines

bigdata examples about spark and flink