Neloy Pramanik Supto

I am an entry-level machine learning and data professional with a strong foundation in Python-based model development and practical computer networking skills. I hold a BSc in Computer Science and Engineering and completed focused coursework in CCNA and MTCNA networking.

I have built and evaluated machine learning models for image and tabular data, applying preprocessing, feature engineering, and CNN-based deep learning for image classification. I use tools such as Python, Pandas, Scikit-learn, TensorFlow, Keras, OpenCV, and Power BI to deliver end-to-end analytics workflows.

On the networking side, I have designed and configured enterprise-style network topologies, implemented IP addressing, subnetting, VLANs, and dynamic routing (OSPF, RIP), and validated configurations with Cisco Packet Tracer and real Cisco devices. I have also developed IoT projects using Arduino, Raspberry Pi, NodeMCU, MQTT and related sensors.

I have co-authored and presented research on machine learning applications, including sleep behavior analysis and hybrid CNN–LSTM frameworks for solar irradiance prediction, demonstrating a commitment to research, interpretability, and data-driven solutions.