Inamdar Zulkarnain

Machine Learning Engineer with practical experience in developing, training, and deploying predictive models for real-world applications. Skilled in Python, TensorFlow, Scikit-learn, and FastAPI, with expertise in data preprocessing, feature engineering, and model optimization. Experienced in building scalable systems and real-time dashboards for data-driven decision-making.

• IEEE Member, 2022
• Published research paper in Industrial Engineering Journal, 6.82
• Published research paper in IJIRSET, 8.699

• Restaurant Management System, React.js, FastAPI, PostgreSQL, Developed a full-stack restaurant management system for managing orders and menus. Built RESTful APIs using FastAPI and integrated PostgreSQL. Designed a responsive frontend using React.js for seamless user experience.
• Plant Leaf Identification System, React.js, FastAPI, TensorFlow, Developed a CNN-based deep learning model to classify plant species from leaf images. Trained CNN model achieving ~90% accuracy on plant dataset. Deployed the model using FastAPI and integrated with React.js for real-time predictions.
• Movie Recommendation System, Python, Pandas, Scikit-learn, Developed a content-based recommendation system using cosine similarity. Performed data preprocessing and feature engineering using Pandas and NumPy. Improved recommendation relevance through optimized similarity techniques.
• Network Monitoring Dashboard, Python, FastAPI, HTML, CSS, JavaScript, Designed a real-time dashboard to monitor system and network metrics. Developed backend APIs using FastAPI to process live data. Built an interactive UI for data visualization using HTML, CSS, and JavaScript.