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💫 About Me:

yassinessadi

Hello there! 👋

I'm passionate about technology and currently immersed in the world of big data, exploring its vast capabilities.

📫 How to Reach Me
You can reach out to me at [email protected]. Whether you want to discuss a project, have a tech-related chat, or just say hi, I'm always open to connecting! Let's build something amazing together.

🌐 Socials:

LinkedIn

💻 Tech Stack:

C# Python JavaScript TypeScript R CSS3 Java PHP Azure AWS .Net Apache Hadoop Apache Kafka Apache Spark Blazor Bootstrap Chart.js jQuery Xamarin FastAPI Flask NodeJS WordPress SASS React Django Express.js MongoDB MySQL ApacheCassandra MicrosoftSQLServer Firebase SQLite Adobe Illustrator Adobe Photoshop Adobe XD Figma Pandas TensorFlow NumPy Plotly scikit-learn Matplotlib GIT LINUX Jira Swagger Trello Postman HTML5

📊 GitHub Stats:



🏆 GitHub Trophies


YASSINE ESSADI's Projects

airflow-weather-orchestration icon airflow-weather-orchestration

This project aims to retrieve data from OpenWeatherMap and orchestrate its processing using Apache Airflow. We collect weather data, perform necessary transformations, and store the results in CSV format on an hourly basis.

background_remover icon background_remover

This project is a powerful and user-friendly solution for removing backgrounds from photos. It utilizes the "rembg" Python library combined with FastAPI to build a robust API that can seamlessly remove backgrounds from images. The front-end is developed using React to create an intuitive user interface for uploading and processing images.

fraud-detection-in-financial-transactions icon fraud-detection-in-financial-transactions

Detect and prevent fraudulent transactions in real-time. Our project utilizes advanced data analysis, focusing on transactional, customer, and external data to enhance security, maintain customer trust, and minimize financial losses.

hadoop-cluster-setup icon hadoop-cluster-setup

this project focuses on setting up Hadoop on a clustered environment, enabling the configuration across multiple nodes for enhanced performance and scalability.

movie-recommendation-als-spark icon movie-recommendation-als-spark

EC-JANE Entertainment launches an innovative film recommendation project utilizing MovieLens data. This project aims to incorporate Big Data analysis and machine learning to enhance movie suggestions, leveraging Apache Spark, Elasticsearch, and a Flask API to provide a personalized and dynamic user experience.

movies-realtime-analysis icon movies-realtime-analysis

This project aims to develop a system capable of analyzing movie reviews in real-time using Kafka for data stream management and Memgraph for the graph database.

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