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Younes Bouchbouk's Projects

animatefx icon animatefx

A library of +70 ready-to-use animations for JavaFX

auto-google-form-quiz-generator icon auto-google-form-quiz-generator

This project showcases how to generate Google Forms dynamically from a React application using Google Apps Script , speech to Text and openia API . The React application sends a questionnaire (in JSON format) as a POST request to a Google Apps Script Web App. The script then creates a new Google Form based on this questionnaire.

data-science icon data-science

Collection of useful data science topics along with code and articles

go-concurrency icon go-concurrency

https://www.udemy.com/course/working-with-concurrency-in-go-golang

go-projects icon go-projects

A repository showcasing my collection of GoLang projects for practicing and enhancing my skills in the language.

nodejs-backend icon nodejs-backend

error handling , Authentication ,Security , models, Controllers

personal-portfolio icon personal-portfolio

Younes Bouchbouk Software Engineer with Gatsby static site generator , tailwindcss animation ...more

re-identification-gui icon re-identification-gui

Detection and re-identification of people in a camera network .* using : Python ( OpenCV , SIFT && ORB algorithm , Tkinter ) , YOLOV4 .

scriptgenius icon scriptgenius

Caption2Script est un projet open source qui utilise l'intelligence artificielle et la vision par ordinateur pour automatiser la génération de scripts percutants pour les publications Instagram. Grâce à une combinaison de modèles d'apprentissage en profondeur et de techniques de traitement du langage naturel

tiktok_clone icon tiktok_clone

TikTok clone React Next Sanity TailwindCss GougleAuth and ...

women-clothing-sentiment-analysis icon women-clothing-sentiment-analysis

A machine learning project that performs sentiment analysis on customer reviews of women's clothing using Natural Language Processing (NLP) techniques, including tokenization, stop-word removal, stemming, and classification using a Multinomial Naive Bayes algorithm. The project is implemented using Python, Pandas, Scikit-learn, and NLTK.

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