You will get Advanced Data Science: Cleaning, ML Modeling, EDA & Visual Insights
Project details
I provide efficient and reliable end-to-end data services with 3 years of hands-on experience in data cleaning, preprocessing, structuring, and machine learning using Python and R. I carefully handle each dataset, ensuring accuracy, reproducibility, and actionable insights tailored to your research or business goals. I deliver not just cleaned data, but also ML model evaluation, visualizations, and well-documented results. I prioritize client satisfaction, clear communication, and high-quality work, making sure your project is completed efficiently and meets your expectations.
Machine Learning Tools
BERT, Google Sheets, Keras, Microsoft Excel, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, R, scikit-learn, SciPy, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$30
|
Standard
$85
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 4 days | 7 days | 10 days |
Number of Revisions | 2 | 3 | 4 |
Number of Model Variations | 0 | 2 | 4 |
Number of Scenarios | 0 | 2 | 4 |
Number of Graphs/Charts | 0 | 3 | 5 |
Model Validation/Testing | - | ||
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$10 - $25
Additional Revision
+$5
Additional Model Variation
(+ 2 Days)
+$10
Additional Graph/Chart
(+ 2 Days)
+$10
Model Validation/Testing
(+ 3 Days)
+$20
Extra dataset
(+ 2 Days)
+$10
Detailed summary report
(+ 2 Days)
+$8
Super fast delivery
(+ 2 Days)
+$17About Hadiur Rahman
Research Data Analyst & Machine Learning Engineer | Python / R
Dhaka, Bangladesh - 2:20 pm local time
Steps for completing your project
After purchasing the project, send requirements so Hadiur Rahman can start the project.
Delivery time starts when Hadiur Rahman receives requirements from you.
Hadiur Rahman works on your project following the steps below.
Revisions may occur after the delivery date.
How I’ll Complete Your Project
1. Review and understand the dataset and client goals. 2. Clean and preprocess the data. 3. Structure dataset for analysis. 4. Apply ML model(s) if requested. 5. Evaluate and visualize results. 6. Deliver a reproducible notebook and summary report.