This is the material for Jose Portilla's Spark and Python for Big Data and ML course.

A course project with implementation of machine learning with spark structured streaming in python

Using PySpark to train machine learning models.

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.

Weather Analysis using PySpark

Cardiovascular Disease Detection using PySpark

Worked on diffrent Spark classification and regression algorithms

12 year nutrient intake analysis across financial classes with PySpark and KMeans clustering

PySpark is a Python API for support Python with Spark. Whether it is to perform computations on large datasets or to just analyze them

Implementation of K-means,Bisecting K-means and Decision Tree in PySpark on the Iris Dataset.

A simple implementation of MLLIB of PySpark to solve a Machine Learning Problem.

Collection of my ML projects using PySpark

Big data management with PySpark

Movie Recommendation using Apache Spark MLlib

Tweet Popularity Analysis using PySpark.

Twitter sentiment analysis based on weather

Scale your Python Code with PySpark in Apache Spark - PyData Charlotte January 2020 Meeting

This notebook contains the usage of Pyspark to build machine learning classifiers (note that almost ml_algorithm supported by Pyspark are used in this notebook)