Isolation Forest on Spark

This project was a joint effort by Lucas De Oliveira, Chandrish Ambati, and Anish Mukherjee to create a song and playlist embeddings for recommendations in a distributed fashion using a 1M playlist dataset by Spotify.

Welcome to some case study of data science projects - (Personal Projects).

Python PMML scoring library for PySpark as SparkML Transformer

classify crime into different categories using PySpark

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My applied big data analytic project with pyspark.

Network traffic classifier based on Apache Spark and MLlib

Example from Spark MLLib (in python)

:bangbang: Handle Big Data for Machine Learning using Python and PySpark, Building ETL Pipelines with PySpark, MongoDB, and Bokeh

Useful scripts and notebooks for Data Science. The project was made by Miquido. https://www.miquido.com/

Sample code for pyspark

Analysis of information about startup companies done using machine learning and data analytics methods to predict the success of the startup companies.

My Practice and project on PySpark

A collection of pyspark exercises

scSPARKL is an Apache spark based pipeline for performing variety of preprocessing and downstream analysis of scRNA-seq data.

A PySpark MLlib classification model to classify songs based on a number of characteristics into a set of 23 electronic genres.

In this Repo, I create a tutorial of PySpark to better understand how to read and manage Big Data.

Transformation of Akamai Logs with Spark ETL and discover of Values and similarities in logs used SparkML and H2O ML

Implementation of movie recommendation systems using Apache Spark ML alternating least squares (ALS)

This repo explains pyspark modules in python. Used to deal with big data more practical handson.

Recommendation System using MLlib and ML libraries on Pyspark

List of useful commands for Pyspark

Micro project on big data technologies via spark

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

This is the final project for the Data Scientist Nanodegree, where our goal is to predict churn for a fictional streaming service called Sparkify.

To Analyze how travelers expressed their feelings on Twitter using pyspark MLlib .Given tweets about six US airlines, the task is to predict whether a tweet contains positive, negative, or neutral sentiment about the airline. This is a typical supervised learning task where given a text string, I have to categorize the text string into predefined categories.

A real-time credit card fraud detection system built with PySpark MLlib that processes transactions through Kafka streams and provides live monitoring via Grafana dashboards.

This repository contains the Notes for Pyspark

Assignment for UoM lesson "Big Data"