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Fiverr Pro
English
$
USD
I will perform data analysis and machine learning using scikitlearn
Data Analyst , Machine Learning
With 4 years of experience in data analysis and Python development, I help businesses turn raw data into clear, actionable insights — from small CSV cleanups to automation pipelines and predictive mod...
About this Gig
Do you need a machine learning model built and evaluated using scikit-learn? I help turn your raw data into working predictive models from data cleaning to a trained, tested, and explained ML solution.
What I offer:
- Data cleaning and preprocessing (handling missing values, encoding, scaling)
- Classification models (logistic regression, decision trees, random forest, SVM)
- Regression and predictive modeling
- Clustering and unsupervised learning
- Model evaluation (accuracy, precision, recall, confusion matrix, cross-validation)
- Feature engineering and selection
- Clear explanation of results not just code, but what it means for your project
Why work with me:
- Strong foundation in Python, pandas,
- and scikit-learn Experience applying ML to real-world projects
- (including computer vision and traffic analysis systems)
- I explain my process clearly, so you understand your model,
- not just receive a black box Fast, reliable deliver with clean, documented code
Send me your dataset and goal (prediction, classification, clustering, etc.) and I'll build a model that fits your needs.
Programming language:
Python
•
SQL
•
Colab
Frameworks:
Scikit-learn
•
DeepPy
•
Google ML Kit
•
PyTorch
•
Panda
APIs:
Microsoft Computer Vision AI
•
Google Cloud Vision API
Tools:
Jupyter Notebook
•
OpenCV
•
Excel
•
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.
