I will build and deploy machine learning and deep learning models as web apps
ML and DL Engineer FastAPI Docker Deployment
About this Gig
Most sellers send you a notebook. I send you a working app.
I build machine learning and deep learning models and deploy them as a FastAPI service with a simple web page, so you can click, test and use them right away.
WHAT I BUILD ML models: classification, regression, churn, risk prediction (scikit-learn) Deep learning: MLP and CNN image classification (PyTorch) Image-upload and live-camera apps REST API with FastAPI, Pydantic validation and Swagger docs Docker container and online deployment (Render, Streamlit, Hugging Face)
PROOF: REAL PROJECTS Plant disease detector: CNN, 15 classes, 88.76% test accuracy, live camera input Student mental health score predictor: tuned Random Forest, R² 0.89, FastAPI + web UI Diabetes risk model: PyTorch + FastAPI + Docker Customer churn API: 7,043 customers, FastAPI + Docker
YOU GET: trained model, clean source code, honest evaluation metrics, API docs and a short README.
Please message me before ordering with your goal and dataset.
Programming language:
Python
Frameworks:
Scikit-learn
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Google ML Kit
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PyTorch
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Panda
APIs:
Microsoft Computer Vision AI
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Other
Tools:
Jupyter Notebook
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OpenCV
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TensorFlow
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Colab
My Portfolio
FAQ
Can you work with images?
Yes. I built a plant disease detector (CNN, 15 classes) where the user uploads a photo or uses the live camera and gets the result with a confidence score.
Do you guarantee accuracy?
No fake promises. Accuracy depends on your data. I show real test results (accuracy, precision, recall, R² or error) and explain the limits.
Do I get the source code?
Yes, in every package.
Can you build health related prediction apps?
Yes, as educational prediction demos. They are not medical diagnosis tools.
What if my data is messy?
Basic and Standard include normal cleaning. Very large or heavily broken data can be quoted by message.

