Bourhou Zaineb

Every website I create is a blend of creativity and functionality, ensuring a seamless user experience. I specialize in HTML, CSS, and JavaScript, crafting responsive designs that look great on any device.

I transform raw data into actionable insights, helping businesses make informed decisions. My expertise includes data visualization, statistical analysis, and machine learning.

I develop robust and scalable software solutions tailored to meet specific business needs. My skills include Python, Java, and C++, ensuring high-quality code and efficient performance.

I design intuitive and engaging user interfaces that enhance user satisfaction. My approach combines aesthetics with usability, ensuring a delightful user experience.

I led a project to build a complete end-to-end sentiment analysis system for YouTube videos. The app extracts comments from any YouTube video, classifies them as positive, neutral, or negative using machine learning, and displays the results through a web interface built with Flask.

BudgetHer is a personal budgeting web app designed specifically to empower women in managing their finances. The app helps users track expenses, set savings goals, and gain better control over their budgets in a simple and visual way. Developed with Flask, HTML/CSS, and SQLite, it offers a user-friendly and mobile-responsive experience.

The Weather App allows users to check real-time weather information for any city worldwide. It displays the current temperature, weather condition, and humidity using the OpenWeatherMap API. Built with HTML, CSS, and JavaScript, the app features a clean, modern, and mobile-responsive interface.

Creating my portfolio website was more than just a technical challenge — it was a way to express who I am as a developer and designer. I used HTML, CSS, and JavaScript to build a site that reflects my personality: clean, creative, and dynamic. I focused on responsive design to ensure it looks great on any device. I also added smooth animations to make the browsing experience more interactive and fun. One of the key goals was to balance visual aesthetics with usability. To make it unique, I added personal touches: my favorite colors, fonts that match my style, and sections that tell my story, like my blog and projects. It’s still evolving, but it’s a space I’m proud to call my own.

When I started learning Machine Learning, I was overwhelmed by the math, libraries, and terminology. Looking back, there are a few things I wish someone had told me:

1. Start small. Don’t rush into complex models — begin with simple datasets and build confidence.
2. Focus on understanding concepts before jumping into code. Know what “overfitting” or “bias” really means.
3. Projects are the best teachers. I learned the most while building my YouTube Sentiment Analysis app.
4. There’s no shame in using tutorials — just make sure you go beyond copying and actually understand the logic.
5. If you’re starting ML as a student, be patient and consistent. The learning curve is real, but it's worth it.

If you’re new to backend development, Flask is a great place to start. It’s a lightweight Python framework that’s perfect for building small to medium web applications. Here’s how I got started:

1. Install Flask :
   I used pip to install Flask in my virtual environment.
2. Create a basic app:
   I set up a simple “Hello World” route to understand how Flask works.
3. Learn about routing:
   I explored how to create different routes and handle requests.
4. Use templates:
   I integrated Jinja2 for rendering HTML templates dynamically.
5. Handle forms:
   I learned how to process form data and validate inputs.
6. Connect to a database:
   I used SQLite for storing data and SQLAlchemy for ORM.
7. Deploy my app:
   Finally, I deployed it on Render, making it accessible online.

Baccalauréat Sciences Physiques, mention très bien. This was a significant milestone that laid the foundation for my future studies in computer science.

Début des études à l'EST (1ère année). This marked the beginning of my journey in software engineering, where I started to explore various technologies and programming languages.

Chef de projet Analyse Sentiments YouTube. I led a project to build a complete end-to-end sentiment analysis system for YouTube videos, enhancing my skills in machine learning and web development.