💻 Data Scientist | Machine Learning Engineer | Data Analyst
I enjoy building machine learning systems, data pipelines, and AI-driven applications that transform raw datasets into practical solutions. My interests lie at the intersection of Data Science, Machine Learning, and Data Engineering.
🔭 Currently working as AI Content & Data Associate at EduCasheer (EdTech Startup)
🧠 Building AI-powered learning systems and automation pipelines
🌱 Currently learning advanced machine learning and data engineering workflows
🤝 Open to collaborating on machine learning, data science, and analytics projects
💬 Ask me about Python, ML, Data Analysis, SQL, and model deployment
Python | SQL | C/C++
Pandas | NumPy | Scikit-learn | PyTorch | Deep Learning | Feature Engineering | EDA
Data Cleaning | Data Preprocessing | Hypothesis Testing | A/B Testing
Matplotlib | Seaborn | Power BI | Tableau
Jupyter Notebook | Git | GitHub | Streamlit | Flask | FastAPI
Built a lightweight PyTorch-like automatic differentiation engine implementing computational graphs and backpropagation.
Key Highlights
- Implemented forward and backward propagation using computational graphs
- Built custom parameter classes and gradient tracking
- Implemented gradient descent optimization
- Demonstrated deep learning fundamentals without external frameworks
Tech: Python, Deep Learning
Developed an AI-driven system to automate study material and educational video generation for an EdTech platform.
Key Highlights
- Built AI-agent pipelines to generate structured study materials
- Automated educational video generation workflows
- Processed and structured learning datasets
- Reduced manual content creation through automation
Tech: Python, AI Agents, Automation
Live:
https://birth-weight-predictor-z6o2.onrender.com/
Repository:
https://github.com/Shariq29/Birth-Weight-Predictor
Highlights
- Built regression models to predict newborn birth weight
- Improved model performance through feature engineering
- Deployed a Flask web application for real-time predictions
Tech: Python, Pandas, Scikit-learn, Flask
Live:
https://bangalore-house-price-predictor-tskt.onrender.com/
Repository:
https://github.com/Shariq29/bangalore-house-price-predictor
Highlights
- Processed 13K+ real estate records
- Achieved 85% prediction accuracy
- Built REST APIs and deployed using Flask, Nginx, and Gunicorn
Tech: Python, Scikit-learn, Flask
Live:
https://customer-churn-predictiongit.streamlit.app/
Repository:
https://github.com/Shariq29/Customer-Churn-Prediction
Highlights
- Modeled telecom customer churn using 7K+ samples
- Handled class imbalance using SMOTE
- Built an interactive Streamlit dashboard for churn prediction
Tech: Python, Pandas, Scikit-learn, Streamlit
EduCasheer – EdTech Startup
Dec 2025 – Present
- Built AI-driven systems for automated study material generation
- Developed pipelines for educational data processing and automation
- Created AI-powered educational videos using automation tools
- Designed and structured online test series datasets
Corizo Edutech
Jan 2023 – May 2023
- Built supervised ML models using Scikit-learn and PyTorch
- Performed EDA, feature engineering, and model validation
- Deployed ML models using Flask, FastAPI, and Streamlit
Bachelor of Technology (B.Tech) – Computer Science
Amritsar Group of Colleges, Punjab
2019 – 2023
📧 Email
shariqsayeed33@gmail.com
🔗 LinkedIn
https://www.linkedin.com/in/shariq-ahmad-a04147234/
🌍 Portfolio
https://shariq-portfolio-eight.vercel.app/
💻 GitHub
https://github.com/Shariq29
⭐ If you find my projects interesting, feel free to connect or collaborate on data science and machine learning projects.