You will get a machine learning model built and deployed with FastAPI
Project details
I will build a machine learning model for your use case and deploy it as a live FastAPI service, so you get a real API endpoint your application can call, not just a model file.
I train the model on your data, optimize it for accuracy, then wrap it in a FastAPI app with endpoints for both single and batch predictions. Everything is containerized with Docker and tracked with MLflow so experiments are logged and results are fully reproducible.
Trained and deployed models achieving up to 90.23% accuracy and 0.89 ROC-AUC on real e-commerce datasets — served via FastAPI with Docker Compose and DVC versioning.
I train the model on your data, optimize it for accuracy, then wrap it in a FastAPI app with endpoints for both single and batch predictions. Everything is containerized with Docker and tracked with MLflow so experiments are logged and results are fully reproducible.
Trained and deployed models achieving up to 90.23% accuracy and 0.89 ROC-AUC on real e-commerce datasets — served via FastAPI with Docker Compose and DVC versioning.
What's included
| Service Tiers |
Starter
$150
|
Standard
$280
|
Advanced
$450
|
|---|---|---|---|
| Delivery Time | 5 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 3 | 5 | 7 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
About M Wajeeh
ML Engineer | Python | Predictive Modeling | Data Analytics
Islamabad, Pakistan - 5:49 am local time
I’m an AI Systems & Machine Learning Engineer focused on building practical, production-ready applications with Python and modern backend technologies.
I can help turn existing Excel-based logic, business rules, or calculation workflows into secure web applications where the core logic stays server-side and users only interact with a clean, simple interface.
My experience includes:
• Python & FastAPI backend development
• React frontend development
• PostgreSQL and database-driven applications
• Authentication and role-based access
• REST APIs and server-side business logic
• Docker, AWS, GitHub Actions, and CI/CD
• Automated testing and validation
• PDF/report generation and data export
• Machine learning model development and deployment
• MLflow and DVC for reproducible ML workflows
I’ve built end-to-end systems involving predictive models, APIs, databases, RAG pipelines, computer vision, AI agents, and deployment. I’m comfortable taking an existing workflow, understanding how it works, translating the underlying logic into maintainable code, and building the application around it.
For projects like yours, I can work across the full stack -- reviewing the existing Excel logic, implementing the calculations server-side, building authentication and user roles, creating the input/output screens, adding audit logging and exports, and deploying the application securely.
I care about clean code, clear communication, and building systems that are reliable and maintainable after delivery.
Steps for completing your project
After purchasing the project, send requirements so M Wajeeh can start the project.
Delivery time starts when M Wajeeh receives requirements from you.
M Wajeeh works on your project following the steps below.
Revisions may occur after the delivery date.
Data review and problem scoping
I review your dataset, confirm the prediction target, check data quality, and define the exact model type and evaluation metrics we'll use before writing a single line of code.
Model training and experimentation
I train and tune the model using MLflow experiment tracking, testing multiple configurations and selecting the best performer based on accuracy, ROC-AUC, or your chosen metric.