You will get a clear analysis and predictions to drive you to taking decisions


Project details
This project involves developing data models and conducting comprehensive analysis to meet the client’s business objectives. The focus will be on gathering, cleaning, and structuring the data, followed by building predictive models that offer insights and improve decision-making processes. The project will include model validation, testing, and documentation to ensure accuracy and reliability. Data source connectivity will be established as needed, and the final deliverables will include detailed reports, charts, and model variations based on the client’s requirements.
Machine Learning Tools
ChatGPT, GitHub Copilot, KNIME, MATLAB, Microsoft Power BI, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, R, scikit-learn, SciPyWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 5 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 2 | 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
+$25 - $100
Additional Revision
+$15
Additional Model Variation
+$20
Additional Scenario
+$15
Additional Graph/Chart
+$20
Model Documentation
+$20
Data Source Connectivity
+$20
Source Code
+$20Frequently asked questions
About Belhsan
Intern Data scientist
Ariana, Tunisia - 7:22 pm local time
Steps for completing your project
After purchasing the project, send requirements so Belhsan can start the project.
Delivery time starts when Belhsan receives requirements from you.
Belhsan works on your project following the steps below.
Revisions may occur after the delivery date.
Data Collection & Preparation
Gather, clean, and structure the necessary datasets from relevant sources.
2. Exploratory Data Analysis (EDA)
Conduct initial analysis to understand patterns, trends, and correlations within the data.
