You will get A complete AI and Machine Learning solution
Project details
You will get a complete Machine Learning solution tailored to your project requirements. Whether you need a classification model, regression model, data preprocessing, or an interactive Streamlit application, I will deliver clean, well-documented, and efficient code.
I work with a wide range of Machine Learning algorithms including Decision Trees, Random Forest, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), XGBoost, CatBoost, LightGBM, Linear Regression, and Gradient Boosting. Every project includes proper data preprocessing, feature engineering, model evaluation, and performance optimization using industry-standard practices.
My goal is to build accurate, reliable, and easy-to-use AI solutions that help transform raw data into meaningful insights. I focus on code quality, clear communication, timely delivery, and ensuring that every project is fully customized to meet your specific requirements.
I work with a wide range of Machine Learning algorithms including Decision Trees, Random Forest, Support Vector Machines (SVM), K-Nearest Neighbors (KNN), XGBoost, CatBoost, LightGBM, Linear Regression, and Gradient Boosting. Every project includes proper data preprocessing, feature engineering, model evaluation, and performance optimization using industry-standard practices.
My goal is to build accurate, reliable, and easy-to-use AI solutions that help transform raw data into meaningful insights. I focus on code quality, clear communication, timely delivery, and ensuring that every project is fully customized to meet your specific requirements.
Machine Learning Tools
NumPy, OpenCV, pandas, Python, Python Scikit-Learn, scikit-learn, SciPy, XGBoostWhat's included
| Service Tiers |
Starter
$10
|
Standard
$25
|
Advanced
$50
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 7 days |
Number of Revisions | 1 | 2 | 4 |
Number of Model Variations | 1 | 3 | 6 |
Number of Scenarios | 1 | 2 | 3 |
Number of Graphs/Charts | 2 | 5 | 7 |
Model Validation/Testing | |||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Frequently asked questions
About Norhan
Machine Learning Engineer
Suez, Egypt - 10:55 pm local time
My expertise includes data preprocessing, exploratory data analysis (EDA), feature engineering, model training, hyperparameter tuning, and performance evaluation. I work with both supervised and unsupervised learning techniques, including classification, regression, clustering, and predictive analytics.
I have experience working with:
Python
Pandas & NumPy
Scikit-learn
XGBoost, CatBoost & LightGBM
Streamlit
Matplotlib & Seaborn
Model Selection & Hyperparameter Tuning (GridSearchCV)
Data Visualization
Services I provide:
Data Cleaning & Preprocessing
Exploratory Data Analysis (EDA)
Feature Engineering
Machine Learning Model Development
Classification, Regression & Clustering
Model Evaluation & Performance Optimization
Interactive Streamlit Dashboards
Well-Documented Python Source Code
I focus on writing clean, maintainable code and delivering reliable, high-quality solutions tailored to each client's needs. Whether you need a predictive model, data analysis, or an AI-powered application, I'm committed to providing accurate results, clear communication, and on-time delivery.
Steps for completing your project
After purchasing the project, send requirements so Norhan can start the project.
Delivery time starts when Norhan receives requirements from you.
Norhan works on your project following the steps below.
Revisions may occur after the delivery date.
Review Requirements
Review the dataset, understand the project objectives, and define the most suitable machine learning approach.
Data Preparation
Clean the dataset, handle missing values, perform feature engineering, and prepare the data for model training.