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- 🧑💻 Passionate AI/ML Engineer with 1.5+ years of hands-on experience in real-world AI systems
- 🔬 Expertise in Predictive Modeling, NLP, Deep Learning, and MLOps
- 🧰 Skilled in Python, TensorFlow, PyTorch, Scikit-learn, Docker, MLflow, Jenkins
- 🚀 Led impactful projects at Asan Innovators, Everlytics, Edunet, YBI, and Postulate InfoTech
- 📊 Adept at transforming data into strategic business insights and deploying solutions at scale
- 🗣 Fluent in English (Professional) with excellent communication and collaboration skills
Python, Pandas, NumPy, TensorFlow, PyTorch, Scikit-learn, SQL, Flask, Docker, Git, GitHub Actions, MLflow, Jupyter, Power BI
Classification, Regression, Clustering, Feature Engineering, CI/CD, Model Validation, Hyperparameter Tuning, Model Deployment, Jenkins
EDA, Data Wrangling, ETL Pipelines, Matplotlib, Seaborn, Business Intelligence, Data Visualization
- Boosted recommendation accuracy by 25% through tailored ML models
- Developed data pipelines & deployed deep learning solutions reducing processing time by 25%
- Designed Tableau dashboards for stakeholders, improving decision speed by 20%
- Built scalable Python-SQL ETL pipelines improving processing by 30%
- Trained PyTorch chatbot models with 90%+ accuracy
- Created Tableau dashboards and drove 12% better performance analysis
- Developed fake news & breast cancer prediction models using NLP & ML
- Implemented statistical pipelines & collaborated in Agile sprints
- Developed ML models using supervised, unsupervised & reinforcement learning
- Performed sentiment analysis & presented results to industry experts
- Worked on deep learning, EDA, and deployment of image/NLP models in real-world settings
- 📚 MCA | Maulana Azad National Urdu University | CGPA: 8.57 (2022–2024)
- 🎓 BCA | Dr. B R Ambedkar University | CGPA: 7.5 (2018–2021)
- Built a full MLOps pipeline using XGBoost, Flask, GitHub Actions, Docker, Render
- RMSE: 5–6 mins | Live: Website
- 88% accuracy with LightGBM + Flask + Jenkins CI/CD
- MLflow for experiment tracking | Dockerized deployment on Render
- Live Demo
- Summarization, Translation, Keyword Extraction, Text-to-Speech
- Used Streamlit, DistilBART, Google APIs, RAKE, and gTTS
- Real-time ML-powered disease detection for Diabetes, Heart, Parkinson's
- Built with SVM, Logistic Regression, Streamlit
- MLOps on GCP (CI/CD, Kubernetes, Jenkins) – 2025
- Data Science Certificate – Pro5, 2024 (Top 5%)
- Machine Learning Masterclass – Pantech, 2022
- AI Job Simulation | Statistics for DS | BI Essentials
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