Spark Java_Examples for all modules including GraphX

Distributed Search and Recommendation with SpringBoot/ElasticSearch/Spark

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

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

Wuzzuf DataAnalysis by java using (SparkSql-Spring-XChart-Spark-ML)

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

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

基于SparkMllib的电影推荐系统

• 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 erro…

Introduction to Apache Spark.

Spark Machine Learning Library - learning and developing Machine Learning algorithms

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.