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I will perform data analysis and machine learning using scikitlearn
Data Analyst , Machine Learning
Hi! I’m Aftab Ahmad, an entry-level Data Analyst with a strong interest in Python, data analysis, and basic machine learning.
I help clients with:
✔ Data cleaning and preprocessing
✔ Python scripts a...
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About This Gig
Ready to turn your CSV data into AI-powered insights? In 2026, data drives successbut only with the right tools. I build custom ML/DL solutions in Python & Scikit-Learn: predictive models, classification, automationdelivered production-ready.
What I Offer:
Data Prep: Clean CSV/Excel, fix missing values, scale features.
Supervised ML: Regression/Classification (Random Forest, SVM, XGBoost).
Unsupervised: Clustering to uncover hidden patterns.
Optimization: Hyperparameter tuning for peak accuracy.
Deep Learning: TensorFlow/Keras neural nets for tough data.
Full Code: Commented Google Colab/Jupyter Notebook.
Why Me? AI expert focused on business impact. Get scalable Python scripts + docs that drive decisions.
Contact before ordering to scope your project!
Lenguaje de programación:
Python
Marcos:
Scikit-learn
•
DeepPy
•
Google ML Kit
•
PyTorch
•
Panda
API:
Google Cloud Vision API
Herramientas:
Jupyter Notebook
•
Colab
FAQ
What format should my data be in?
I primarily work with CSV, Excel (.xlsx), and JSON files. However, I can also connect to SQL databases or Google Sheets. If your data is "unstructured" (like a collection of text files), please message me first so we can discuss the preprocessing required.
Do I need to clean my data before sending it to you?
No! Data cleaning and preprocessing are included in all my packages. I will handle missing values, remove duplicates, and perform feature encoding using Pandas and Scikit-Learn to ensure your dataset is ready for high-accuracy modeling.
What specific Machine Learning libraries do you use?
My primary stack includes Scikit-Learn (sklearn) for traditional ML (Random Forest, SVM, Regression) and Pandas/NumPy for data manipulation. For the Premium package, I also use TensorFlow or Keras if your project requires Deep Learning or Neural Networks.
Will I be able to run the code myself?
Absolutely. I deliver the final project as a Google Colab notebook (.ipynb) or a Python script (.py). I include step-by-step comments so that even if you aren't a programmer, you can run the model and see the results with one click.
How do you ensure the model is accurate?
I use professional evaluation metrics such as Accuracy, Precision-Recall, F1-Score, and Mean Squared Error (MSE). For the Standard and Premium packages, I perform Cross-Validation and Hyperparameter Tuning to ensure the model performs well on "unseen" data, not just your current file.
