I will build and train ml models rf, xgboost, svm, knn and more

I can work on a wide range of projects including predictive modeling, classification, regression, data analysis, and automation tasks. If you’re unsure, just send me your dataset and project details.

I work with Random Forest, K-Nearest Neighbors, XGBoost, Support Vector Machine, Logistic Regression, Decision Trees, and more. I select the best algorithm based on your data and project goals.

I need your dataset or sample data, project objectives, and any specific requirements or preferred algorithms. The clearer your inputs, the better the results.

Yes! You will receive clean, commented Python code (or Jupyter Notebook) that you can run and reuse.

Absolutely. I handle missing values, feature scaling, encoding, and imbalanced data handling so the model is ready for training.

Yes, I perform hyperparameter tuning using techniques like grid search or random search to improve your model’s performance.

Delivery depends on dataset size and project complexity. Typical small projects take 1–3 days, while larger projects may take longer. I always provide an estimated delivery time before starting.

Yes, I can work with small to medium structured datasets. For extremely large datasets, we can discuss preprocessing or splitting the data for efficient training.