I will optimize your machine learning model with feature engineering
about me
About this Gig
Improve your machine learning model with effective feature engineering and optimization. I will clean and transform your data, select relevant features, compare ML models, tune hyperparameters, and evaluate performance using Python, Pandas and Scikit-learn. Youll receive clean code and clear results.
Programming language:
Python
Frameworks:
Scikit-learn
•
Panda
My Portfolio
FAQ
1. What file formats do you accept for the dataset?
I work with CSV, Excel (.xlsx), JSON, Parquet and SQL exports. If your data is in another format, message me first — I can usually handle it.
2. Do you work with deep learning or neural networks?
This gig focuses on classical machine learning with Scikit-learn (Random Forest, XGBoost, SVM, Logistic Regression, etc.). For deep learning projects (TensorFlow/PyTorch), please contact me for a custom offer.
3. Can you handle large datasets?
Yes, I can work with datasets up to several GB. For very large datasets (10GB+), please contact me first so we can discuss the best approach.
4. Will I get the source code?
Yes, all packages include the full Python/Jupyter Notebook source code, cleanly commented so you can reuse and modify it.
5. Do you deploy the model or build an API?
No, deployment and API integration are not included in this gig. Check my other gig for ML model deployment services.
6. What if my dataset is confidential?
I fully respect confidentiality. I'm happy to sign an NDA before starting, and I never share or reuse client data.
7. Can you improve an existing model I already have?
Absolutely. Just share your current code/notebook and I'll analyze it, then apply feature engineering and optimization to improve its performance.
