Popular GitHub Repositories for Mllib

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

CTR prediction model based on spark(LR, GBDT, DNN)

Isolation Forest on Spark

商品类目预测，使用 Spring Boot 开发框架和 Spark MLlib 机器学习框架，通过 TF-IDF 和 Bayes 算法，训练出一个商品类目预测模型。该模型可以根据商品名称自动预测出商品类目。项目对外提供 RESTFul 接口。

:star2: :sparkles: Analyze and visualize Twitter Sentiment on a world map using Spark MLlib

UC Berkeley team's submission for RecSys Challenge 2018

Random Forests in Apache Spark

A Deep Neural-Network based (Deep MLP) Stock Trading System based on Evolutionary (Genetic Algorithm) Optimized Technical Analysis Parameters (using Apache Spark MLlib)

以Spring Boot框架为载体，通过集成hanLP、neo4j、spark-mllib实现基于电影知识图谱的简易问答系统。

Natural Korean Processor for Apache Spark

大数据框架 Spark MLlib 机器学习库基础算法全面讲解,附带齐全的测试文件

dllib is a distributed deep learning library running on Apache Spark

使用Spark的MLlib、Hbase作为模型、Hive作数据清洗的核心推荐引擎,在Spark on Yarn测试通过

Develop ML models predict taxi trip duration in NYC. Ranked : Top 6% | RMSLE : 0.377 (Kaggle) | #DS

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

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

Bayesian hyperparamter tuning for Spark MLLib

Sentiment Analysis and Data Visualization

Slides, code and more for my class: Data Analytics and Machine Learning on Big Data