Phoenix - Your AI AssistantBuild and deploy a machine learning API with FastAPI and Docker
Delivery in
4 days
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What you get with this Offer
Turn your Machine Learning model into a working, tested and deployed prediction service—not just another notebook.
I will handle the workflow from data preparation and model development to FastAPI, Docker, MLOps, CI/CD and deployment. You will receive a reproducible API ready to connect to your website, application or internal system.
WHAT I WILL DO
✓ Understand your business objective and success criteria
✓ Review, clean and prepare your dataset
✓ Build and compare suitable ML models
✓ Track experiments and metrics with MLflow
✓ Select the final model using performance and business value
✓ Register and version the selected model
✓ Create a FastAPI prediction service
✓ Add input validation and error handling
✓ Connect one standard database when required
✓ Package the application with Docker
✓ Create essential model and API tests
✓ Configure GitHub Actions CI/CD
✓ Automate testing, Docker builds and deployment
✓ Deploy to one agreed hosting platform
✓ Add logging, a /health endpoint and basic monitoring
The model will not be selected on accuracy alone. Where relevant, I will consider false-prediction costs, class imbalance, response time and operational constraints.
YOU WILL RECEIVE
• One trained and evaluated ML model
• Clean, documented Python source code
• MLflow experiment tracking and model versioning
• FastAPI with /predict and /health endpoints
• One standard database integration when required
• Dockerfile and dependency configuration
• Model and API tests
• GitHub Actions CI/CD workflow
• Automated deployment to one agreed platform
• Swagger API documentation
• Deployment and usage instructions
• Seven days of support for delivery-related bugs
BASE OFFER SCOPE
• One CSV or Excel dataset
• Up to 50,000 rows and 30 input features
• One classification or regression objective
• One final CPU-based model
• One API, database integration, GitHub workflow and deployment environment
NEED SOMETHING MORE CUSTOM?
For Deep Learning or GPU models, multiple databases, real-time ingestion, scheduled retraining, drift monitoring, Kubernetes, enterprise security or multiple endpoints, please message me before ordering. I will recommend a tailored scope and quote.
Please send your objective, dataset, expected API inputs and outputs, database requirements, traffic estimate and preferred hosting platform.
I will handle the workflow from data preparation and model development to FastAPI, Docker, MLOps, CI/CD and deployment. You will receive a reproducible API ready to connect to your website, application or internal system.
WHAT I WILL DO
✓ Understand your business objective and success criteria
✓ Review, clean and prepare your dataset
✓ Build and compare suitable ML models
✓ Track experiments and metrics with MLflow
✓ Select the final model using performance and business value
✓ Register and version the selected model
✓ Create a FastAPI prediction service
✓ Add input validation and error handling
✓ Connect one standard database when required
✓ Package the application with Docker
✓ Create essential model and API tests
✓ Configure GitHub Actions CI/CD
✓ Automate testing, Docker builds and deployment
✓ Deploy to one agreed hosting platform
✓ Add logging, a /health endpoint and basic monitoring
The model will not be selected on accuracy alone. Where relevant, I will consider false-prediction costs, class imbalance, response time and operational constraints.
YOU WILL RECEIVE
• One trained and evaluated ML model
• Clean, documented Python source code
• MLflow experiment tracking and model versioning
• FastAPI with /predict and /health endpoints
• One standard database integration when required
• Dockerfile and dependency configuration
• Model and API tests
• GitHub Actions CI/CD workflow
• Automated deployment to one agreed platform
• Swagger API documentation
• Deployment and usage instructions
• Seven days of support for delivery-related bugs
BASE OFFER SCOPE
• One CSV or Excel dataset
• Up to 50,000 rows and 30 input features
• One classification or regression objective
• One final CPU-based model
• One API, database integration, GitHub workflow and deployment environment
NEED SOMETHING MORE CUSTOM?
For Deep Learning or GPU models, multiple databases, real-time ingestion, scheduled retraining, drift monitoring, Kubernetes, enterprise security or multiple endpoints, please message me before ordering. I will recommend a tailored scope and quote.
Please send your objective, dataset, expected API inputs and outputs, database requirements, traffic estimate and preferred hosting platform.
What the Freelancer needs to start the work
Please provide:
• A clear description of your business objective
• Your CSV or Excel dataset
• The target variable you want to predict
• Examples of the expected API inputs and outputs
• Your preferred hosting platform
• Access to your GitHub repository or permission to create one
• Database type and connection requirements, if applicable
• Your expected traffic or prediction volume
• Any performance or response-time requirements
• Access to the required hosting and database environments after purchase
Please message me before ordering so I can confirm that your data, database and deployment requirements fit the base offer.