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I will do eda and data preprocessing for your ml models
Pakistan
I speak English
Ai Engineer
Hi! I’m Hasnat — an AI & Machine Learning Engineer with hands-on experience in Deep Learning, Computer Vision and NLP.
I specialize in:
• Building ML & Deep Learning models (classification, regress...
About this Gig
Are you preparing data for machine learning models? I will perform professional Exploratory Data Analysis (EDA) and data preprocessing to make your dataset clean, insightful, and ML-ready!
Using Python (Pandas, NumPy, Matplotlib, Seaborn), I'll deliver:
- Detailed data exploration with statistics and visualizations
- Identification of patterns, outliers, and correlations
- Thorough data cleaning (handling missing values, duplicates, encoding)
- Feature engineering and train-test split (in higher packages)
- Clean, commented Jupyter notebook + PDF report
Perfect for data scientists, students, startups, or anyone building ML models. I ensure high-quality work with clear insights to help you understand your data better.
100% satisfaction guaranteed with revisions. Send me your dataset (CSV, Excel, etc.) and requirements let's get your data ready for success!
Programming language:
Python
Tools:
Jupyter Notebook
•
OpenCV
•
TensorFlow
•
Excel
•
Colab
FAQ
What file formats do you accept?
I accept CSV, Excel (.xlsx), JSON, SQL dumps, or common data format. Just send me the file!
What tools do you use?
I primarily use Python with Pandas, NumPy, Matplotlib, Seaborn, and Scikit-learn for professional and efficient results.
Do you provide the source code?
Yes! You'll receive a fully commented Jupyter notebook with all the code and explanations.
How many revisions are included?
Unlimited revisions until you're 100% satisfied (within reasonable scope).
Can you handle large datasets?
Yes, I can work with datasets of any size. For very large files, we can discuss the best approach.
Do you offer custom requirements?
Absolutely! Contact me before ordering if you have specific needs (e.g., specific visualizations or techniques).
