You will get I will build a multi-agent AI system to automate your ML workflow
Project details
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Looking to automate your entire machine learning workflow — not just get a single model?
I built AutoDS AI, a multi-agent AI system (Python + Google Gemini) where six specialized agents collaborate to handle your data end-to-end: a Data Loader Agent validates your dataset, a Cleaning Agent handles missing values and quality issues, an EDA Agent generates statistical summaries and visualizations, a Feature Engineering Agent prepares your data for modeling, a Machine Learning Agent trains and evaluates multiple models to find the best performer, and an Insight Agent explains results in plain business language.
You're not just getting a model — you're getting an automated pipeline built on Python, Pandas, NumPy, Scikit-learn, XGBoost, and Streamlit.
Whether your goal is churn prediction, sales forecasting, classification, or regression, I'll tailor this system to your dataset and business question — delivering clear visualizations, trained models, and insights you can act on.
Clean documentation and clear communication throughout, with source code available on select packages.
Looking to automate your entire machine learning workflow — not just get a single model?
I built AutoDS AI, a multi-agent AI system (Python + Google Gemini) where six specialized agents collaborate to handle your data end-to-end: a Data Loader Agent validates your dataset, a Cleaning Agent handles missing values and quality issues, an EDA Agent generates statistical summaries and visualizations, a Feature Engineering Agent prepares your data for modeling, a Machine Learning Agent trains and evaluates multiple models to find the best performer, and an Insight Agent explains results in plain business language.
You're not just getting a model — you're getting an automated pipeline built on Python, Pandas, NumPy, Scikit-learn, XGBoost, and Streamlit.
Whether your goal is churn prediction, sales forecasting, classification, or regression, I'll tailor this system to your dataset and business question — delivering clear visualizations, trained models, and insights you can act on.
Clean documentation and clear communication throughout, with source code available on select packages.
Machine Learning Tools
Microsoft Excel, NumPy, pandas, Python, scikit-learn, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$280
|
|---|---|---|---|
| Delivery Time | 3 days | 6 days | 8 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 0 | 2 | 4 |
Number of Scenarios | 1 | 1 | 2 |
Number of Graphs/Charts | 4 | 7 | 10 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$15 - $45
Additional Revision
+$12
Additional Model Variation
(+ 2 Days)
+$25
Additional Scenario
(+ 2 Days)
+$30
Additional Graph/Chart
(+ 1 Day)
+$10
Model Validation/Testing
(+ 2 Days)
+$25
Model Documentation
(+ 1 Day)
+$18
Source Code
(+ 1 Day)
+$20
Extra Dataset / Additional Analysis
(+ 2 Days)
+$40Frequently asked questions
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EM
Eric M.
Aug 15, 2025
Social Media Data Analyst (YouTube, Facebook, TikTok, Instagram)
Extremly skilled guy and clients satifaction is his priority! He did the job and even when beyond. Thank you Muza and thanks Upwork.
About Muzamil
Data Scientist | ML, EDA & Data Cleaning | Python Expert
Muzaffargarh, Pakistan - 10:42 pm local time
I help businesses turn raw data into decisions — through clean analysis, predictive modeling, and machine learning.
My core work:
Data cleaning, EDA, and analysis in Python
Supervised learning: classification, regression, churn prediction, demand forecasting
Unsupervised learning: clustering, segmentation, anomaly detection
Gradient boosting models (XGBoost, LightGBM, CatBoost)
Deployment via Streamlit and FastAPI, so results are usable, not just notebooks
I also build LLM-powered workflows and AI agents to automate parts of the analysis pipeline — useful when a project needs automated reporting or repetitive analysis handled reliably.
Featured project — AutoDS AI: a multi-agent platform (Python + Google Gemini) that automates data cleaning, feature engineering, EDA, model selection, and reporting.
I focus on validated, production-ready solutions — not just model outputs. If you have data and need it turned into something actionable, let's talk.
Steps for completing your project
After purchasing the project, send requirements so Muzamil can start the project.
Delivery time starts when Muzamil receives requirements from you.
Muzamil works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements Review.
I will review your dataset, business objectives, and project requirements to determine the best machine learning approach
Data Processing & Model Development
I will clean and preprocess the data, perform exploratory data analysis (EDA), engineer features, and build the most suitable machine learning model.