I will build production ready time series forecasting models
AI,ML and Data Science Specialist,Data Annotation, Python, CVAT
About this Gig
A predictive model is useless if it only lives in a Jupyter Notebook. You need production-ready AI.
Instead of just running basic statistical forecasts, I specialize in transforming raw historical data into scalable, deployed forecasting engines. From hyperparameter tuning to real-time API endpoints, I build end-to-end pipelines ready to be integrated into your business logic, whether you are predicting retail sales or high-frequency IoT sensor data.
Advanced Forecasting & ML:
- Deep Learning & Modern AI: Neural Prophet (Specialty), LSTM, GRU.
- Traditional & Statistical: ARIMAX, GMM, GARCH.
- Tree-Based: XGBoost, Random Forest.
- Hyperparameter Tuning: State-of-the-art optimization using Optuna for maximum accuracy.
The Production Pipeline (The Real Value):
- Model Registry: Tracking and versioning with MLflow.
- Time-Series Databases: Integration with TimeScaleDB or InfluxDB.
- Backend API: Exposing your model via FastAPI for seamless software integration.
- Visualization: Standalone interactive web apps (Streamlit, Plotly) or live monitoring dashboards (Grafana).
IMPORTANT: Every dataset and business goal is unique. Please message me before ordering.
My Portfolio
FAQ
ill my proprietary business data be kept confidential?
Absolutely. I treat all client data with the strictest confidentiality. I am happy to sign an NDA before we begin. Once the project is completed and the pipeline is handed over, all raw data is permanently deleted from my local environments.
What format should my data be in, and what is required?
I accept CSV, Excel, JSON, or SQL database dumps. For time series forecasting, your dataset must contain at least two columns: a clear chronological time/date indicator and the target variable you want to predict (e.g., daily sales, hourly server load, or stock price).
Can you guarantee 100% accuracy for future predictions?
No honest data scientist can guarantee perfect future accuracy, as real-world events (like sudden market crashes or viral trends) introduce unpredictable noise. However, I use rigorous cross-validation and hyperparameter tuning (via Optuna) to mathematically ensure the model provides the most accura
Do you host the model for me, or do I host it?
: My Premium package provides you with a fully containerized Docker setup. This means I build the complete, deployable software package, which you (or your engineering team) can instantly run on your own AWS, Azure, or local company servers to ensure you have full ownership of the system.
What is the difference between the Standard API and Premium Pipeline?
The Standard package gives you the trained neural network wrapped in a FastAPI endpoint so your app can send it data and get a prediction back. The Premium package is a full ecosystem: it includes the API, a time-series database (InfluxDB/TimeScale) to store incoming data, and a live Grafana web das

