You will get Custom Forecasting Model for Your Business Data
Project details
Do you need accurate forecasts to make better business decisions? I will design and deliver a custom machine learning forecasting model tailored to your data and use case.
Whether you need sales forecasting, demand prediction, financial time series analysis, or resource planning, I’ll build a solution that helps you plan with confidence.
Whether you need sales forecasting, demand prediction, financial time series analysis, or resource planning, I’ll build a solution that helps you plan with confidence.
Machine Learning Tools
Azure Machine Learning, NumPy, pandas, Python, Python Scikit-Learn, scikit-learn, SciPy, SQL, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$125
|
Advanced
$250
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 3 | 5 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 1 | 3 | 4 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Additional Model Variation
(+ 1 Day)
+$40About Heythem
Machine Learning Engineer
M'Sila, Algeria - 3:20 pm local time
My strengths:
Tabular ML: XGBoost, LightGBM, CatBoost, feature engineering, rolling/lag features
Time-series forecasting and prediction pipelines
Computer vision: ViT, DINO, segmentation, copy-move forgery detection
Data cleaning, analysis, and building end-to-end ML solutions
I deliver fast, accurate, and practical solutions. If you need someone to build models, analyze data, or create ML pipelines, I can help.
Steps for completing your project
After purchasing the project, send requirements so Heythem can start the project.
Delivery time starts when Heythem receives requirements from you.
Heythem works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Understanding
-Review the dataset provided by the client -Clarify target variable, forecast horizon, and business context -Identify potential data quality issues
Data Cleaning & Feature Engineering
-Handle missing values, outliers, and formatting -Create time-based features, lags, rolling windows, and categorical encodings -Split data into training and validation sets