You will get a custom machine learning model for your dataset in Python
Project details
I will build a custom machine learning model using Python to help you uncover insights from your data. Whether it's classification, regression, or clustering, I’ll provide a complete solution including preprocessing, model training, evaluation, and clear visualizations. Perfect for students, startups, or businesses who need reliable ML solutions.
Tools: Python, Scikit-learn, Pandas, NumPy, Matplotlib.
Tools: Python, Scikit-learn, Pandas, NumPy, Matplotlib.
Machine Learning Tools
MATLAB, Microsoft Excel, MLflow, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, scikit-learn, XGBoostWhat's included
| Service Tiers |
Starter
$15
|
Standard
$30
|
Advanced
$60
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 3 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 0 | 1 | 4 |
Model Validation/Testing | |||
Model Documentation | - | - | |
Data Source Connectivity | - | ||
Source Code | - |
About Abdullah
Junior Machine Learning & Web Developer | Python | AI Intern |
Lahore, Pakistan - 5:20 am local time
I’ve completed hands-on projects in:
Unsupervised and supervised ML (classification, clustering, recommendations)
Python, Scikit-learn, Pandas, NumPy
Web development using HTML, CSS, JavaScript
I'm looking for opportunities where I can:
Assist with ML model development and data cleaning
Build basic recommender systems
Help with web app integration or front-end styling
I'm committed, detail-oriented, and eager to learn with every project. Let's build something awesome together!
Steps for completing your project
After purchasing the project, send requirements so Abdullah can start the project.
Delivery time starts when Abdullah receives requirements from you.
Abdullah works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Collection
I’ll review your dataset and understand your goals (e.g., predict outcome, segment data, recommend items).
Data Preprocessing
Handle missing values, encode categorical data, normalize/scale features if needed.