Popular GitHub Repositories for Pyspark Mllib

Isolation Forest on Spark

Recommendation System using MLlib and ML libraries on Pyspark

Big data application of Machine Learning concepts for sentiment classification of US Airlines tweets. The focus is on the usage of pyspark libraries (ml-lib) on big data to solve a problem using Machine Learning algorithms and not about the choice of algorithm used in the ML model creation. It also involves data pre-processing using NLP techniques, cross-validation and parameter-grid builder.

This repo shows how to review and derive information from datasets using Python. First, get an overview of data science and how it open source libraries like Python can be used for your data analysis need. Then, discover how to set up labs and data interpreters. Next, learn about how you can use pandas, NumPy, and SciPy for numerical processing, scientific programming, and extensive data exploration. With these options at your disposal, you'll be ready for the following code which focuses on making predictions using machine learning tools, data classifiers, and clusters. The repo concludes with a look at big data and how PySpark can be used for computing.

Final project from "Machine Learning at Scale" (W261) in UC Berkeley's Data Science Masters program

Exploring spark machine learning capabilities

This repo contains implementations of PySpark for real-world use cases for batch data processing, streaming data processing sourced from Kafka, sockets, etc., spark optimizations, business specific bigdata processing scenario solutions, and machine learning use cases.

ML Monitoring with EvidentlyAI