I will build machine learning and deep learning models
ML and DL Engineer FastAPI Docker Deployment
About this Gig
Struggling to turn your data into a working, deployed AI solution? I can help.
I'm Rayhan, a Machine Learning & Deep Learning engineer who builds models that actually ship not just notebooks that sit on a shelf.
WHAT I OFFER:
- Data preprocessing & exploratory analysis
- ML model development (classification, regression) using scikit-learn
- Deep Learning models using PyTorch
- Model testing, optimization & fine-tuning
- Deployment as a REST API using FastAPI
- Containerization with Docker for easy, portable deployment
- Cloud deployment for live, production-ready systems
RECENT PROJECTS:
- Diabetes risk prediction (PyTorch neural network, 97%+ accuracy)
- Customer churn prediction API (FastAPI + Docker)
- Income & house price prediction models (deployed via Streamlit)
WHY WORK WITH ME:
- Clean, documented, production-ready code
- Clear communication throughout the project
- Focus on real-world deployment, not just accuracy on paper
- On-time delivery
Programming language:
Python
Frameworks:
Scikit-learn
•
PyTorch
•
Panda
APIs:
Other
Tools:
Jupyter Notebook
•
Colab
My Portfolio
FAQ
Do you build the model from scratch or use pre-trained ones?
Depends on your project. For custom prediction tasks I train models from your data; for NLP/vision tasks I can also fine-tune pre-trained models when it's more efficient.
Will I get the source code?
Yes, clean and documented source code is included in every package.
Can you deploy the model so I can use it in my own app?
Yes — I deploy models as a REST API using FastAPI, containerized with Docker so it runs reliably anywhere (Standard & Premium packages).
What do you need from me to start?
Your dataset (or data source), the prediction goal, and any specific format/tech requirements. Message me before ordering so I can confirm scope.
Do you offer revisions if the model needs improvement?
Yes, each package includes a set number of revisions for tuning and adjustments based on your feedback.

