aymane-maghouti

HR-Data-Pipeline-Azure

This project is a comprehensive data engineering solution that extracts HR data from a GitHub repository, performs data transformations using Azure services, and creates an interactive HR dashboard using Power BI. The goal is to enable HR professionals and decision-makers to gain insights from the HR data for better workforce management.

Loan-Credit

This project aims to develop a machine learning model using Logistic Regression for classifying loan credit applications as either approved or rejected.

Youtube-data-pipeline

The project aims to automate the extraction of data from a YouTube channel, transform the data into a suitable format, and make it available for analysis through a Power BI dashboard. By following a structured ETL process, this project streamlines data retrieval, preparation, and visualization.

Contact_Management

This project is a desktop application developed using Java and JavaFX frameWork for managing contacts and groups.

E-student

This is a student management system project built using Python and the Tkinter library.

ETL-Club-Datai

Draw your first ETL

Human-Resources-data-pipeline

This ETL (Extract, Transform, Load) project aims to extract human resources data, clean it using PL/SQL and SQL, integrate it into a Snowflake data warehouse on Azure Cloud using Informatica, and visualize the insights in Power BI.

Real-Time-Data-Pipeline-Using-Kafka

This project implements a real-time data pipeline using Apache Kafka, Python's psutil library for metric collection, and SQL Server for data storage. The pipeline collects metrics data from the local computer, processes it through Kafka brokers, and loads it into a SQL Server database. Additionally, a real-time dashboard is created using Power BI.

aymane-maghouti

aymane-maghouti.github.io

Jumia-data-pipeline

This project focuses on extracting data from the Jumia website using Beautiful Soup, storing it in an Excel file with Pandas, and then transferring the data to a PostgreSQL database using SQLAlchemy and Pandas.

Logistic-Regression-Club-Datai

classification with logistic regression

Logistic-regression-Project

This project is about exploring the logistic regression algorithm

Machine-Learning-basics

This is a basic repository which contains a simple application of machine learning algorithms and some statistical methods for data analysis

Machine-Learning-From-Scratch

This project implements various machine learning algorithms from scratch using Python and NumPy, without relying on external libraries such as TensorFlow, Keras, or scikit-learn. The implemented algorithms include classification, regression, clustering, and basic neural network models.

Mobile-Data-Hive-Insights

This project demonstrates the process of extracting data from a MySQL database, transferring it using Apache Sqoop, storing it in Hive Data warehouse (the data actually is store in Hadoop Distributed File System (HDFS)), and performing analysis using Hive Query Language (Hive QL) (it is a language close to SQL). Then visualize the data in Power BI,

Real-time-Computer-Performance-Dashboard

This project aims to capture, store, and visualize real-time system performance metrics through an end-to-end data pipeline. By leveraging Python, MySQL, SQL Server, and Power BI, we've created a comprehensive solution to enhance decision-making.

Real_Time_DB-People_Count

sales-data-pipeline

This ETL (Extract, Transform, Load) project demonstrates the process of extracting data from a SQL Server database, transforming it using Python, orchestrating the data pipeline with Apache Airflow (running in a Docker container), loading the transformed data into Google BigQuery data warehouse, and finally creating a dashboard using Looker Studio.

Sentiment-Analysis-for-Jumia-Reviews-and-Smartphone-Price-Prediction-System

The project focuses on customer sentiment analysis for Jumia, aiding informed online decisions. It collects and analyzes product comments to determine sentiments and implements a decision-making algorithm. Additionally, it includes product price prediction system using regression techniques.

Weather-Data-Explorer

the project focus on retrieving weather data, analyzing and processing it, and presenting the results through data visualization and a Flask web application.