Spark After Dark
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Recommendationsystem | 190 | 6 years ago | Python | |||||||
| Book recommender system using collaborative filtering based on Spark | ||||||||||
| Spark | 119 | 2 years ago | JavaScript | |||||||
| GitHub Stars Sparklines ⚡️ | ||||||||||
| Streaming Matrix Factorization | 100 | 8 years ago | 4 | apache-2.0 | Scala | |||||
| Distributed Streaming Matrix Factorization implemented on Spark for Recommendation Systems | ||||||||||
| Spark_als | 68 | 5 years ago | mit | Java | ||||||
| 基于spark-ml,spark-mllib,spark-streaming的推荐算法实现 | ||||||||||
| Recommendmoteur | 57 | 6 years ago | Scala | |||||||
| 电影推荐系统、电影推荐引擎、使用Spark完成的电影推荐引擎 | ||||||||||
| Movie Recommender Demo | 50 | 2 years ago | 1 | apache-2.0 | Jupyter Notebook | |||||
| This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to topic where they are consumed by a spark streaming job running on IBM BigInsights (hadoop). | ||||||||||
| Php Statsd | 30 | 10 years ago | PHP | |||||||
| simple statsd library and CI spark | ||||||||||
| Movies Analytics In Spark And Scala | 24 | 3 years ago | apache-2.0 | |||||||
| Data cleaning, pre-processing, and Analytics on a million movies using Spark and Scala. | ||||||||||
| Spark After Dark | 24 | 9 years ago | Scala | |||||||
| Click Through Rate Prediction | 21 | 8 years ago | 1 | apache-2.0 | Scala | |||||
| Kaggle's click through rate prediction with Spark Pipeline API | ||||||||||
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