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Hi, I'm Ares👋

Software Developer & AI Engineer with a strong focus on Machine Learning, Computer Vision, and Cybersecurity-related systems.

I enjoy building end-to-end ML pipelines — from data preprocessing and feature engineering to model evaluation and real-time prediction.

Currently working on projects involving image processing, CNN-based models, and ML-driven applications, and creating structured learning guides for students and self-learners.


🧠 Core Expertise

  • Machine Learning & Deep Learning
  • Computer Vision & Image Processing
  • Model Training & Evaluation (CNN, SVM, Hybrid CNN–SVM)
  • Web-based deployment of ML systems
  • ML-based Security Systems (SQL Injection Detection, Cybersecurity Foundations)

🧭 Guides & Learning Roadmaps

I also create beginner-to-intermediate guides and roadmaps to help students and self-learners understand AI, Machine Learning, and Computer Vision through structured learning paths and real projects.


⚙️ Tech Stack

💻 Core Languages

Python JavaScript HTML5 CSS3 PHP Java C%23


🌐 Web & Backend Frameworks

React Node.js Express.js Flask Streamlit TailwindCSS Bootstrap


🤖 Machine Learning & AI

TensorFlow PyTorch Keras Scikit Learn XGBoost YOLO OpenCV MediaPipe OpenAI


📊 Data Science & Visualization

NumPy Pandas Matplotlib Seaborn


🔐 Databases & Security

MySQL PostgreSQL


🌐 Deployment & Platforms

Docker Vercel Google Colab Kaggle Anaconda


🛠️ Developer Tools & Design

Git GitHub VS Code Postman Figma Canva Adobe Photoshop


🚀 Featured Projects & Live Demos

🍺 Detecting Alcohol Intoxication Using Image Processing

An AI-based facial image analysis system that compares CNN, SVM, and a Hybrid CNN–SVM model to classify intoxicated vs. normal facial states using facial features.

Tech Stack: Python · OpenCV · CNN · SVM · Hybrid CNN–SVM · Gradio · Hugging Face Spaces

Live Demo: 👉 https://huggingface.co/spaces/ares-coding/alcohol-intoxication-demo

Source Code: 👉 https://github.com/ares-coding/detecting-alcohol-intoxication-using-image-processing

Deployed as an interactive Gradio demo showcasing the end-to-end ML workflow: image input → inference → prediction visualization.


🔐 Malicious URL Detection System

A machine learning–based system designed to detect and classify malicious URLs by analyzing extracted URL features and patterns, helping prevent phishing and web-based attacks.

Tech Stack: Python · Machine Learning · Scikit-learn · XGBoost · Feature Engineering · Streamlit

Source Code: 👉 https://github.com/ares-coding/malicious-url-detection-using-ml

Includes a Streamlit-based interface demonstrating real-time URL analysis and classification.


🛡️ SQL Injection Attack Detection

A security-focused project demonstrating real-world SQL injection vulnerabilities and detection using pattern analysis. Highlights how improper query handling can bypass authentication and shows mitigation through secure query practices.

Tech Stack: Python · MySQL · SQL · Pattern Analysis · Cybersecurity

Source Code: 👉 https://github.com/ares-coding/sql-injection-attack-detection

Demonstrates both vulnerable and secured query implementations using real SQL queries.


📩 Spam Message Detection App

A machine learning–powered application that identifies spam messages using Natural Language Processing (NLP). Analyzes message content and classifies text as spam or legitimate in real time.

Tech Stack: Python · NLP · Machine Learning · Scikit-learn · Text Classification

Source Code: 👉 https://github.com/ares-coding/spam-message-detection

Focused on text preprocessing, feature extraction, and classification accuracy for message filtering.


##GitHub Stats

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