Machine Learning | Deep Learning | Generative AI | Backend Systems

I am a software engineering student focused on machine learning, deep learning, generative AI, and backend development.
I enjoy building systems where data, models, and APIs work together to solve real problems. My focus is on understanding how modern AI systems work and applying them in practical use cases.
I am currently learning and building in ML, DL, LLM-based systems, and backend engineering.

Programming: Python, SQL, Bash/Shell scripting Machine Learning: Supervised & Unsupervised Learning, Classification, Regression, Clustering, Feature Engineering, Model Evaluation & Cross-Validation, PCA, Time Series, Anomaly Detection
Deep Learning & AI: Neural Networks (MLP, CNN ), Backpropagation, Optimization, Transformers , LLM fundamentals, Prompt Engineering, RAG GenAI / LLM Systems: LLM app design, RAG pipelines, Vector DBs , Context engineering, Agent systems , LLM evaluation
Backend Development: FastAPI, Django, REST APIs, PostgreSQL, ML/LLM API integration, Auth basics, System design basics
Tools & Frameworks: NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch (basic–intermediate), Hugging Face, Git, Postman, Jupyter
Math for ML: Linear Algebra, Probability & Statistics, Calculus (gradients & optimization intuition)

• Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG)
• Agent-based and multimodal AI systems
• Explainable AI (XAI) and model evaluation
• AI system design with backend integration
• Healthcare applications of AI
• Building and deploying LLM-based applications
• Improving deep learning fundamentals
• Moving toward production-ready ML systems

📖 Medium: https://medium.com/@subisurbiee

Build, Learn, Iterate.