I will build an end to end machine learning and mlops pipeline
Data Science Engineer, AI, ML, Computer Vision and RAG Systems
Informazioni su questo servizio
I will build an end-to-end Machine Learning and MLOps pipeline designed for reliable, reproducible and production-oriented workflows.
I can help you automate data processing, model training, experiment tracking, validation, deployment and monitoring using modern MLOps tools.
Depending on your package, the solution can include Apache Airflow orchestration, MLflow experiment tracking, Docker containerization, model evaluation, API integration, monitoring and production deployment.
Typical use cases include:
-Automated ML training pipelines
-MLflow experiment tracking
-Airflow workflow orchestration
-Model validation and optimization
-Dockerized ML applications
-Prediction APIs
-Model monitoring
-Production-ready ML systems
Technologies may include Python, SQL, MLflow, Apache Airflow, Docker, XGBoost, Scikit-learn, PostgreSQL, MinIO and FastAPI.
Please contact me before ordering if your project requires a complex cloud architecture, large-scale deployment or custom infrastructure.
Linguaggio di programmazione:
Python
•
SQL
Framework:
Scikit-learn
•
Altro
API:
Altro
Strumenti:
Quaderno jupyter
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MLflow
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Colab
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Altro
Il mio portfolio
Altri servizi della categoria Data science e ML offerti da me
FAQ
What type of MLOps projects can you build?
I can build automated ML pipelines, experiment tracking systems, model training workflows, deployment pipelines, APIs and monitoring solutions.
Can you automate model training with Airflow?
Yes. I can create automated Airflow workflows for data processing, model training, validation, deployment and reporting.
Can you integrate MLflow into my project?
Yes. I can integrate MLflow for experiment tracking, metrics, model artifacts and model lifecycle management.
Will I receive the source code?
Yes. Source code is included according to the selected package.
Can you deploy the pipeline to the cloud?
Yes. Cloud deployment is available in the Premium package or through a custom offer depending on the infrastructure.

