You will get a predictive model or forecast from your data
Project details
You have data. I'll tell you what it's predicting.
I take your raw CSV or database export and deliver a complete ML pipeline — from messy data to a trained model with clear visual results your team can actually use.
What makes this different: I don't just hand you a Jupyter notebook and disappear. You get a plain-English report explaining what the model found, what it means for your business, and how confident we should be in the predictions.
I've built ML pipelines for demand forecasting, anomaly detection, and churn prediction — using Random Forest, XGBoost, and Prophet depending on what your data needs.
My background in both software engineering and data science means I can also deploy your model into a working web app if needed — not just a notebook.
Perfect for: sales forecasting, customer churn risk, demand prediction, inventory planning, or any tabular dataset where you need answers fast.
I take your raw CSV or database export and deliver a complete ML pipeline — from messy data to a trained model with clear visual results your team can actually use.
What makes this different: I don't just hand you a Jupyter notebook and disappear. You get a plain-English report explaining what the model found, what it means for your business, and how confident we should be in the predictions.
I've built ML pipelines for demand forecasting, anomaly detection, and churn prediction — using Random Forest, XGBoost, and Prophet depending on what your data needs.
My background in both software engineering and data science means I can also deploy your model into a working web app if needed — not just a notebook.
Perfect for: sales forecasting, customer churn risk, demand prediction, inventory planning, or any tabular dataset where you need answers fast.
Machine Learning Tools
pandas, Python, PyTorch, scikit-learn, TensorFlowWhat's included
| Service Tiers |
Starter
$50
|
Standard
$75
|
Advanced
$120
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 3 | 5 | 8 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Muhammad
Data Scientist & ML Engineer | Predictive Models . Analytics Dashboard
Rawalpindi, Pakistan - 4:37 am local time
I'm a Data Scientist with 3+ years of hands-on experience building full-stack data products. My edge is simple: I understand both sides of the problem. I can build the machine learning model and deploy it into a working application your team can actually use — not just a notebook that lives on someone's laptop.
What I actually do:
Predictive Modeling & Forecasting:
I build regression and classification models that answer real business questions — which customers will churn, what demand looks like next month, where the anomalies are hiding. Tools: Python, scikit-learn, XGBoost, Random Forest, Prophet.
Data Analysis & Dashboards:
I take raw, messy data and turn it into visual dashboards with clear takeaways. I work in Tableau, Streamlit, and Plotly — whichever format your team will actually open and use.
End-to-End ML Pipelines:
From raw CSV to trained model to live prediction interface. I've built pipelines covering demand forecasting, anomaly detection, and churn prediction — with proper train-test splits, model evaluation, and documentation.
A few things I've built:
→ Autonomous drone delivery simulation with Random Forest demand forecasting (R² = 0.87) and real-time anomaly detection across 4 classifiers
→ Customer churn prediction system using Focal Loss + SHAP explainability — caught data leakage in a published 2024 paper and fixed it
→ 110M-parameter GPT model trained across 1, 2, and 4-GPU setups using ColossalAI — achieved 2.85× speedup
→ Blood pressure analysis pipeline implemented in both Python and R with identical results
My software engineering background (React, Node.js, Spring Boot, MySQL) means I'm not just a data scientist who can't ship anything. If your ML solution needs a frontend or an API layer, I can build that too.
I work best with clients who have real data and a real decision to make. If that's you, send me a message — I'll tell you within 24 hours whether I can help and exactly how.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Cleaning
I review your dataset, handle missing values, encode categories, and prepare it for modeling. I'll confirm scope and ask any clarifying questions before starting.
Model Training & Evaluation
I train and compare multiple models (Random Forest, XGBoost, or Prophet), evaluate accuracy with RMSE/AUC metrics, and select the best performer for your data.