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Building AI & Data Solutions
πŸ€–
Building AI & Data Solutions

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malik8154/README.md

πŸ‘¨β€πŸ’» Shahmeer Rashid

πŸš€ AI & Machine Learning Engineer | Turning Data into Intelligent Solutions

Turning raw data into meaningful insights through AI, ML, and software engineering.
Passionate about building intelligent, data-driven, and impactful applications.


πŸ”­ Current Work

  • Developing AI-powered applications with real-world impact in computer vision, NLP, and predictive analytics
  • Building real-time ML systems for classification, object detection, and anomaly detection
  • Implementing end-to-end ML pipelines: data collection β†’ preprocessing β†’ modeling β†’ deployment
  • Integrating AI models with web and mobile applications for practical usability
  • Optimizing deep learning models for performance and inference speed

🌱 Learning & Growth

  • Exploring advanced Deep Learning architectures (CNNs, Transformers, LSTMs)
  • Enhancing skills in real-time computer vision and object detection frameworks
  • Learning cloud deployment and MLOps practices for scalable AI systems
  • Experimenting with vector databases, semantic search, and AI-powered applications
  • Strengthening expertise in Python, TensorFlow, PyTorch, and production-ready AI pipelines

πŸ› οΈ Skills & Expertise

Programming & Scripting
Python C++ Java JavaFX SQL Flutter

Web Development
HTML5 CSS3 JavaScript React TailwindCSS

Machine Learning & AI
Scikit-learn TensorFlow Keras PyTorch Pandas NumPy NLTK OpenCV Matplotlib Seaborn

Databases & Deployment
PostgreSQL Docker

Development Tools & Practices
Git Agile VS Code Linux


πŸ“Œ Pinned Projects

πŸ’° Smart Solution for Finance and Investment Optimization (Full-Stack Web App) (Capstone Project)
A comprehensive financial management platform designed to empower users with personalized budgeting, savings optimization, investment tracking, and financial insights using advanced ML models.

πŸ“Œ Due to university policy, the project isn't publicly hosted on GitHub β€” view details on LinkedIn.

πŸ”— View the project details on LinkedIn


πŸ”₯ Real-Time Fire Detector (Computer Vision Project)
A real-time fire detection system built with TensorFlow, Keras, and OpenCV. Detects fire instantly from webcam or Android phone camera feeds, triggers audible alerts, and logs fire events automatically.

Key Features:

  • Real-time detection with webcam or mobile IP camera
  • Audible alerts and event logging (fire_alerts.log)
  • Lightweight CNN model optimized for fast inference

Repository & Model:


πŸ€– ML Interview Q&A Bot
An AI-powered Q&A bot for interview preparation, leveraging FAISS, Transformers, and Streamlit for real-time question answering and context retrieval.

πŸ”— View Repository


Other Projects

  • Snake Game (Python) – A classic Snake game developed with Python’s Pygame library, featuring dynamic gameplay and score tracking. πŸ”— View Repository
  • Coffee Land (C++) – A coffee shop application with menu handling, billing system, and customer interaction. πŸ”— View Repository
  • Mathematics Quiz System (Assembly) – Quiz game with score tracking. πŸ”— View Repository

πŸ“Š GitHub Stats

GitHub Stats
Top Languages


πŸ’¬ Ask Me About

  • Python for Data Science and automation
  • Data Preprocessing & Visualization techniques
  • NLP & Computer Vision fundamentals
  • Best practices for AI-ready repositories

πŸ“« Connect with Me

LinkedIn GitHub Email


⚑ β€œAI is not only about algorithms β€” it’s about building systems that empower people and teams to make better decisions.”

Popular repositories Loading

  1. AICP-Internship-Week1-NumPy-Exercises AICP-Internship-Week1-NumPy-Exercises Public

    Solutions to Week 1 NumPy exercises from the AICP Internship, covering array creation, random number generation, matrix operations, and statistical analysis.

    Jupyter Notebook

  2. AICP-Internship-Week2-Pandas-Exercises AICP-Internship-Week2-Pandas-Exercises Public

    Week 2 AICP Internship tasks focusing on Pandas for data manipulation, filtering, grouping, and aggregation.

  3. AICP-Internship-Week3-Data-Visualization AICP-Internship-Week3-Data-Visualization Public

    Week 3 AICP Internship tasks using Matplotlib and Seaborn to create visualizations for datasets, including bar charts, scatter plots, and histograms.

  4. AICP-Internship-Week4-McDonalds-EDA AICP-Internship-Week4-McDonalds-EDA Public

    Week 4 AICP Internship exercises focusing on cleaning raw datasets, handling missing values, and performing exploratory data analysis (EDA).

  5. AICP-Internship-Week5-Instagram-EDA AICP-Internship-Week5-Instagram-EDA Public

    Analysis of Instagram engagement metrics from Week 5 of the AICP Internship, including content performance and audience interaction insights.

  6. AICP-Internship-Week6-BirthRate-EDA AICP-Internship-Week6-BirthRate-EDA Public

    Week 6 AICP Internship project implementing predictive modeling techniques for forecasting trends using Python and scikit-learn.