Machine Learning Library MLlib Guide MLlib is Spark’s machine learning (ML) library. Its goal is to make practical machine learning scalable and easy. At a high level, it provides tools such as:

ML Algorithms: common learning algorithms such as classification, regression, clustering, and collaborative filtering Featurization: feature extraction, transformation, dimensionality reduction, and selection Pipelines: tools for constructing, evaluating, and tuning ML Pipelines Persistence: saving and load algorithms, models, and Pipelines Utilities: linear algebra, statistics, data handling, etc.

Please feel free to contact me if you have any questions with this repo:)

使用Pyspark 实现几个机器学习的例子：

1. 基于ALS 推荐算法 [完成]
2. 使用Spark的分类器 [完成]
3. 使用Spark的回归器 [完成]
4. 使用Spark的ML库 [完成]

如果对代码仓有任何问题，欢迎联系我：）