You will get a custom classification model with accurate predictions
Project details
I build tailored classification models that turn your data into smart decisions. Backed by hands-on project experience and a strong foundation in machine learning, I deliver reliable, well-documented solutions that align with your goals.
Machine Learning Tools
pandas, Python, Python Scikit-Learn, scikit-learnWhat's included
| Service Tiers |
Starter
$200
|
Standard
$350
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 7 days | 14 days | 25 days |
Number of Revisions | 2 | 3 | 4 |
Model Validation/Testing | |||
Model Documentation | |||
Data Source Connectivity | - | - | - |
Source Code | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$30
Source Code
+$150About Dickson
Data Science & Machine Learning Enthusiast | Python & Scikit-Learn
Cotonou, Benin - 11:00 pm local time
Currently, I specialize in Python programming and have foundational skills in Pandas, NumPy, Matplotlib, and Scikit-Learn. I'm also developing my expertise in TensorFlow to tackle more advanced deep learning projects.
Some of my recent projects include:
- Heart Disease Prediction using machine learning models like Logistic Regression and Random Forest.
- Bulldozer Price Prediction using regression techniques on historical sales data.
While I am still honing my analytical and problem-solving skills, I am deeply committed to delivering reliable, data-driven solutions and continuously improving my expertise. Whether you need to analyze data, build predictive models, or implement machine learning algorithms, I am here to help you achieve your goals.
Steps for completing your project
After purchasing the project, send requirements so Dickson can start the project.
Delivery time starts when Dickson receives requirements from you.
Dickson works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review and Preprocessing
I review the dataset for completeness and cleanliness, performing necessary preprocessing tasks (e.g., handling missing values, encoding categorical variables, scaling features).
Model Selection and Training
I select the most suitable classification model(s) and train them on the dataset using best practices for optimization and hyperparameter tuning.