I will build a machine learning classification model in python with evaluation
About this Gig
I will build reliable machine learning classification models in Python, with proper evaluation and clear results.
I focus on correct methodology not inflated accuracy so you get results that actually make sense.
What I can help you with:
- Machine learning classification models (Scikit-learn)
- Clean, reproducible Jupyter Notebooks
- Proper train/test separation (no data leakage)
- Evaluation using accuracy, precision, recall, F1-score
- Model comparison and interpretation
Packages explained:
Basic
Build one ML classification model assuming a pre-cleaned dataset, with evaluation.
Standard
End-to-end ML workflow including preprocessing, multiple models, and clear evaluation.
Premium
Advanced ML analysis with model comparison, interpretation, and clear recommendations.
Deliverables:
- Jupyter Notebook (.ipynb)
- Evaluation metrics and explanations
- Source code and documentation (Standard & Premium)
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This gig focuses on analysis and modeling, not deployment or APIs.
If you're unsure which package fits your needs, feel free to message me before ordering.
Programming language:
Python
Frameworks:
Scikit-learn
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Panda
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Other
Tools:
Jupyter Notebook
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Colab
FAQ
What type of machine learning do you work on?
I work on classical machine learning classification problems using Python and scikit-learn.
Do you handle messy or raw datasets?
Yes, but only in the Standard and Premium packages. The Basic package assumes a pre-cleaned dataset.
Do you deploy models or build APIs?
No. This gig focuses on analysis, modeling, evaluation, and interpretation, not deployment or APIs.
What deliverables will I receive?
You will receive a Jupyter Notebook with code, evaluation metrics, and explanations. Source code and documentation are included in Standard and Premium.
I’m not sure which package to choose.
Feel free to message me with details about your dataset and goals, and I’ll help you choose the right package.

