You will get Business-Optimized Machine Learning Classification for Insightful Decisions
Project details
You will receive a custom-built machine learning classification model designed to give your business actionable insights and enhance decision-making. With extensive experience in data science and machine learning, I specialize in delivering high-quality, data-driven solutions tailored to your unique objectives. My approach ensures a reliable model that aligns with your business goals, including a full refund policy if you're not satisfied with the accuracy. Whether you're aiming to improve customer segmentation, predict outcomes, or drive operational efficiency, I’ll provide a model that’s both powerful and adaptable, ensuring it supports your goals effectively.
Machine Learning Tools
Google AutoML, Microsoft Excel, NumPy, pandas, Python Scikit-Learn, PyTorch, scikit-learn, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$25
|
Standard
$50
|
Advanced
$75
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 2 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 1 | 2 | 3 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Frequently asked questions
About Suliman
Machine Learning Python Developer
London, United Kingdom - 2:04 pm local time
Machine Learning: Highly skilled in binary and probability classification tasks
I am dedicated to delivering high-quality, scalable, and intuitive applications, integrating seamless user authentication and session tracking to create a personalized user experience.
Steps for completing your project
After purchasing the project, send requirements so Suliman can start the project.
Delivery time starts when Suliman receives requirements from you.
Suliman works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Understanding
I will review the provided dataset to understand its structure, quality, and any initial transformations required to prepare it for modeling.
Data Cleaning & Preprocessing
Clean the dataset, handle missing values, and perform feature engineering as needed for optimal model performance.