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I will clean and preprocess your research or ml dataset using python
Python Data Analyst Data Cleaning and ML Support
Hi, I’m Inshara, a Machine Learning Engineer and Software Engineering graduate. I help students, researchers, and startups clean and prepare their data, engineer features, and build Python-based machi...
Über diesen Service
Do you have messy Excel or CSV data that needs to be ready for analysis or machine learning? I can help. I will clean, preprocess, and prepare your dataset so it is accurate, organized, and ready to use.
What I offer:
- Remove duplicates, fix missing or incorrect values
- Standardize formats and ensure consistency
- Encode categorical variables if needed
- Prepare your data for analysis or machine learning
- Deliver a clean, ready-to-use dataset
I focus on delivering reliable, professional work and make sure your data is usable and well-structured. Please send your dataset before ordering so we can discuss your requirements and ensure the best results.
FAQ
What file formats do you accept?
I accept Excel files (.xlsx, .xls) and CSV files. If you have another format, please contact me before ordering.
What size datasets can you handle?
I can efficiently clean small to medium datasets (up to ~50,000 rows). For very large datasets, please contact me first to discuss.
Do you prepare data for machine learning?
Yes, I can preprocess your data, handle missing values, encode categorical variables, and create features to make it ready for analysis or machine learning.
Can you handle multiple datasets in one order?
Yes. For additional datasets beyond the package limit, you can use the “Additional Items” extra.
Will I get a clean, ready-to-use dataset?
Yes. I ensure your dataset is cleaned, deduplicated, properly formatted, and ready for analysis or modeling.
Can I request revisions?
Yes. Each package includes 2–3 revisions depending on the package. You can also purchase additional revisions if needed.
Do you explain the changes made to my dataset?
Absolutely. I provide a brief summary of all cleaning, preprocessing, and formatting steps so you understand what was done.
