Machine Learning & Data Analysis with Python (Prediction, Classification, Time Series)

I build and compare machine learning models on tabular data using Python (scikit-learn, XGBoost, TensorFlow/PyTorch).

What you get:
- Data cleaning and preprocessing (missing values, outliers, class imbalance)
- 2-3 models trained and compared (e.g. Random Forest, Neural Network, XGBoost)
- Evaluation with the right metrics (Recall, F1, ROC-AUC, RMSE, etc.)
- Clear report with charts and well-documented code
- Optional: deployment as an API (FastAPI/Docker)

Good for: medical data prediction, price forecasting (time series), customer or sales prediction, and academic/research projects.

How it works:
1. Send me a short description of your dataset and goal
2. I confirm scope, timeline and final price
3. I deliver the models, report and code

Starting price is for a small dataset (up to ~10,000 rows). Larger or more complex projects are quoted individually.