Spark Java_Examples for all modules including GraphX
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Updated
Dec 8, 2017 - Java
Spark Java_Examples for all modules including GraphX
A collection of “cookbook-style” scripts for simplifying data engineering and machine learning in Apache Spark.
Recommendation engine in Java. Based on an ALS algorithm (Apache Spark). Train a new model after N seconds.
Implementation of Recommender Systems (RS) using Apache Spark MLlib on movielens dataset
Introduction to Apache Spark.
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.
Big Data Project - SSML - Spark Streaming for Machine Learning
Introductory Big Data concepts using Spark framework and different libraries
We generate potential customer leads for businesses on yelp using big data and machine learning
Distributed Search and Recommendation with SpringBoot/ElasticSearch/Spark
Scala Library for extracting useful information from trained Spark Model (DecisionTreeClassificationModel)
User, Event, and Predictive Metric Dashboard on 2GB/month of log files from Brackets IDE
An implementation of K-means algorithm using Spark MLlib and Scala
Solving Kaggle Titanic with Pyspark libraries
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