I will build a machine learning model for prediction and classification
Machine Learning Engineer, Predictive Modeling and Data Analysis
About this Gig
Are you looking for a reliable machine learning solution for your prediction or classification problem?
I specialize in classical machine learning building clean, accurate, and well-documented models using Python. My work covers the full pipeline: data cleaning, exploratory data analysis, feature engineering, model training, and evaluation.
What I can build for you:
Classification models (churn, risk, fraud, etc.)
Regression models (price prediction, forecasting, etc.)
Data preprocessing & feature engineering
Model evaluation with clear performance metrics
Documented, production-ready code
Tools & tech I use:
Python, scikit-learn, XGBoost, Random Forest, Pandas, NumPy
Why work with me:
️ Clear communication throughout the project
️ Documented code, not just a black-box notebook
️ Honest scoping I'll tell you if your data or goal needs adjusting before I start
️ Fast turnaround without cutting corners on accuracy
I don't do deep learning or web development I focus purely on classical ML done right, so you get a model you can actually trust and explain.
Programming language:
Python
•
MLflow
Frameworks:
Scikit-learn
•
PyTorch
•
Panda
APIs:
Azure Face API
Tools:
Jupyter Notebook
•
TensorFlow
•
Excel
•
Colab
FAQ
What kind of data do you need from me?
A structured dataset (CSV or Excel) with the column you want to predict clearly identified. If you're not sure your data is ready, message me first — I'll review it.
Do you do deep learning or neural networks?
No — I specialize in classical machine learning (Random Forest, XGBoost, regression, etc.), which is faster, more interpretable, and often more accurate for structured/tabular data than deep learning.
Will I get the source code?
Yes, source code is included in Standard and Premium packages, and available as a paid add-on with Basic.
Can you deploy the model so I can use it online?
Not currently — I focus on model development and delivery as documented code/notebooks. (Update this once you've learned deployment.)
What if my project needs revisions after delivery?
What if my project needs revisions after delivery?

