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amldataprepdocs

Documentation for Microsoft Azure Machine Learning Data Preparation

banking-security-enhancement-using-pyspark

Utilizing PySpark, we devised a robust fraud detection system analyzing Capital One's daily banking data to identify potential fraud. Leveraging PySpark SQL for data analysis and MLlib for precise predictive modeling, our team demonstrated expertise in crafting scalable solutions, fostering enhanced banking security

employee-attrition-analysis-and-prediction

This project undertakes the critical task of analyzing and predicting employee attrition, offering insights into the factors that influence employee turnover. Utilizing a dataset sourced from Kaggle, the project encompasses extensive data analysis and predictive modeling, aimed at helping organizations retain talent.

healthcare-cost-prediction-and-analysis

This project utilizes a dataset hosted on S3 to analyze the healthcare costs associated with various individual factors such as age, BMI, smoking status, and more. The script involves data wrangling, exploratory data analysis (EDA), visualization, and predictive modeling using various machine learning algorithms.

ist722dbt

notesofyoutubesqlseries

pyspark-project-lending-club-data

This repository contains Jupyter notebooks demonstrating the data cleaning and transformation process for a Lending Club dataset using PySpark. The project is designed to leverage the power of Apache Spark to process and clean large datasets efficiently.

python-exercises

redis_example_matrix_workout

retail-dbms-api

shiny-app-for-terrorism-data-analysis-and-visualization

The Terrorism Data Analysis project aims to provide an in-depth analysis of terrorism activities globally. This project encompasses various stages including data processing, exploratory data analysis (EDA), application of machine learning algorithms, and data visualization.

textblob-ar

Arabic support for textblob