You will get Sales/Demand with a Python Model + Accuracy Report
Project details
I will build a professional sales or demand forecasting model that helps you predict future performance with measurable accuracy.
Using Python (Prophet / XGBoost / scikit-learn), I clean your data, engineer predictive features, and compare models using MAE and MAPE to ensure reliable results.
You will receive clear forecast charts, scenario planning (best/base/worst), and ready-to-use CSV outputs for dashboards or reporting.
My approach is business-focused — not just code, but insights you can act on.
Using Python (Prophet / XGBoost / scikit-learn), I clean your data, engineer predictive features, and compare models using MAE and MAPE to ensure reliable results.
You will receive clear forecast charts, scenario planning (best/base/worst), and ready-to-use CSV outputs for dashboards or reporting.
My approach is business-focused — not just code, but insights you can act on.
Machine Learning Tools
Microsoft Excel, Microsoft Power BI, MLflow, NumPy, pandas, Python, scikit-learn, SciPy, SQLWhat's included
| Service Tiers |
Starter
$99
|
Standard
$299
|
Advanced
$699
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 3 | 3 |
Number of Graphs/Charts | 1 | 4 | 6 |
Model Validation/Testing | - | - | - |
Model Documentation | - | - | - |
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Frequently asked questions
About Aduewa
Machine Learning Engineer | Forecasting, Classification, NLP | Python,
Colchester, United Kingdom - 7:58 am local time
What I can deliver for you:
• Forecasting (ARIMA/Prophet/XGBoost) with accuracy tracking (MAE/MAPE)
• Classification & scoring models (churn, fraud, risk) with explainability (SHAP)
• Data cleaning + feature engineering + model training pipelines
• Model evaluation + bias checks + clear recommendations
• Dashboards & reporting (Power BI / Excel) connected to model outputs
Tools: Python (pandas, scikit-learn), SQL, Jupyter, Git, Power BI/Excel.
Steps for completing your project
After purchasing the project, send requirements so Aduewa can start the project.
Delivery time starts when Aduewa receives requirements from you.
Aduewa works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Preparation
I review your dataset, validate date structure, clean missing values, and prepare it for modeling.
Feature Engineering & Modeling
I create predictive features (lags, rolling metrics, seasonality) and train forecasting models (Prophet/XGBoost).