You will get Predictive Data Analysis & Machine Learning Reports in Python and Tableau
Project details
You will get a powerful machine learning solution built in Python, with interactive data visualisations and dashboards in Tableau to communicate insights and predictions.
Whether you're trying to predict customer behaviour, detect fraud, forecast sales, or uncover patterns in your data, I’ll deliver a complete end-to-end data science project tailored to your specific needs.
Whether you're trying to predict customer behaviour, detect fraud, forecast sales, or uncover patterns in your data, I’ll deliver a complete end-to-end data science project tailored to your specific needs.
Machine Learning Tools
Microsoft Power BI, OpenCV, Python, scikit-learn, TableauWhat's included
| Service Tiers |
Starter
$100
|
Standard
$190
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 4 days | 6 days | 10 days |
Number of Revisions | 2 | 3 | 4 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 3 | 5 |
Number of Graphs/Charts | 3 | 6 | 11 |
Model Validation/Testing | |||
Model Documentation | - | - | |
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$10 - $30
Additional Revision
+$10
Additional Model Variation
(+ 2 Days)
+$20
Additional Scenario
(+ 2 Days)
+$20
Additional Graph/Chart
(+ 2 Days)
+$10
Model Documentation
(+ 2 Days)
+$30About Chikunie
Data Analyst
Benin City, Nigeria - 11:22 pm local time
Steps for completing your project
After purchasing the project, send requirements so Chikunie can start the project.
Delivery time starts when Chikunie receives requirements from you.
Chikunie works on your project following the steps below.
Revisions may occur after the delivery date.
Understand the Client's Requirements
Review the client's dataset and business goals. I’ll analyse your project brief and data to fully understand what you're trying to predict or visualise, ensuring the solution aligns with your goals.
Data Cleaning & Preparation
I will clean and preprocess your dataset, handle missing values, encode variables, and prepare it for machine learning.