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

Spark Java_Examples for all modules including GraphX

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

Distributed Search and Recommendation with SpringBoot/ElasticSearch/Spark

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

中文电商商品类目预测

Data Driven Sentiment Insight into Twitter(X) Trends | Kafka | Spark | Spark MLlib | Docker

EverAnalyzer is my thesis in the Department of Digital Systems of the University of Piraeus. EverAnalyzer is a platform for collecting, preprocessing, processing and analyzing Big Data from the Twitter platform.

Big Data Project - SSML - Spark Streaming for Machine Learning

Big Data Analytics Project using Apache Spark for Predicting Severity of Car Accidents in the USA

No description provided.

Utilized SparkML and Scikit-Learn train several machine learning models for distinguishing fraudulent and legitimate transactions. The machine learning models are then utilized to make predictions on Kafka-generated real-time data streams. Built an interface for displaying these predictions in real-time using the Streamlit framework.

We generate potential customer leads for businesses on yelp using big data and machine learning

This is a repository i have created to put up some of the knowledge i have gained around Big Data Technologies especially Spark, GraphX etc.

Work in-progress NBA Game Predictor using Spark

for learning apache spark and mlib library

No description provided.

Spark Machine Learning Library - learning and developing Machine Learning algorithms

使用SpringBoot & ElasticSearch 及ELK组件 & Spark ML Lib构建一个仿大众点评的千人千面推荐系统（不是

• Developed a Recommender System for restaurants by performing analysis on data preprocessed from Yelp Dataset. • Used Altering Least Squares method with Matrix Factorization and Neighborhood Model to train and build the Recommender System. • Tested the Recommender System with multiple rounds of Cross Validation technique and 16% prediction error is observed

基于SparkMllib的电影推荐系统

Introduction to Apache Spark.

Spark in Action

SparkMLlibDeepLearn scala source algorithm analysis

Implementation of Recommender Systems (RS) using Apache Spark MLlib on movielens dataset

Training with Spark MLlib and Spark ML

No description provided.

User, Event, and Predictive Metric Dashboard on 2GB/month of log files from Brackets IDE

Solving Kaggle Titanic with Pyspark libraries

Python-SparkMLib-ALS Project