You will get ML Model for Prediction and Data Analysis with Visualisations and Insights


Project details
I provide clear and structured machine learning solutions tailored to your needs, with a strong focus on understanding and practical results. Unlike generic implementations, I combine solid mathematical foundations with real-world applications to deliver accurate models, meaningful insights, and clean, well-documented Python code. I specialise in supporting academic projects and helping clients achieve reliable, high-quality outcomes.
Machine Learning Tools
NumPy, pandas, Python, Python Scikit-Learn, scikit-learn, SciPyWhat's included
| Service Tiers |
Starter
$20
|
Standard
$35
|
Advanced
$60
|
|---|---|---|---|
| Delivery Time | 1 day | 2 days | 3 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 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
+$20 - $50About Muhammad Zeeshan
AI, Machine Learning & Python Expert | Robotics, Computer Vision, MSc
Edinburgh, United Kingdom - 3:24 am local time
I specialise in explaining difficult concepts in a clear, structured way, combining strong mathematical foundations with practical implementation. My expertise includes machine learning models, data analysis, computer vision, and autonomous systems.
I can help with:
Machine learning and AI assignments
Python programming (beginner to advanced)
Computer vision projects
Mathematical foundations of AI
Exam preparation and coursework support
I focus on delivering accurate, well-structured, and high-quality work while ensuring clear understanding for the client.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Zeeshan can start the project.
Delivery time starts when Muhammad Zeeshan receives requirements from you.
Muhammad Zeeshan works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements Review
Review dataset, problem description, and client expectations.
Data Preprocessing
Clean and prepare the data for modelling.
