You will get Data analysis, Predictive Modelling with Python - Accurate Results
Project details
I will deliver a full data analysis and predictive modeling pipeline using Python. This includes data cleaning, exploratory analysis, and building a machine learning model tailored to your target. You will receive a clean Jupyter Notebook with code, charts, and well-explained results. My goal is to help you get clear, accurate, and actionable insights from your data.
Machine Learning Tools
Keras, Microsoft Power BI, NumPy, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, TensorFlow, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$100
|
Advanced
$175
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 0 | 1 | 2 |
Number of Scenarios | 1 | 1 | 2 |
Number of Graphs/Charts | 3 | 5 | 7 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$20 - $60
Additional Revision
+$30
Additional Model Variation
(+ 1 Day)
+$50
Additional Graph/Chart
(+ 2 Days)
+$50
Model Validation/Testing
(+ 3 Days)
+$60
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Narihan O.
Oct 12, 2025
Statistical analysis
About Maha
ML engineer/ Data scientist
Cairo, Egypt - 12:49 pm local time
.
I specialize in:
🔹 Predictive Modeling & Time Series Forecasting
🔹 Machine Learning (Classification, Regression, Clustering)
🔹 Data Cleaning, Feature Engineering, and EDA
🔹 Python, Scikit-learn, Pandas, NumPy, XGBoost
🔹 Power BI, Tableau, Excel – for interactive dashboards
🔹 SQL – for efficient data manipulation
I build lean, production-ready ML models in Python to solve real business problems: demand forecasting, churn prediction, and failure detection. Clean feature engineering, rigorous validation (CV, holdout, calibration), and clear, decision-oriented reporting. Deliverables you
Let’s bring your data to life!
Steps for completing your project
After purchasing the project, send requirements so Maha can start the project.
Delivery time starts when Maha receives requirements from you.
Maha works on your project following the steps below.
Revisions may occur after the delivery date.
Data Review & Cleaning
I will review your dataset structure, identify issues like missing values, incorrect types, or outliers, and perform thorough data cleaning to prepare it for analysis.
Exploratory Data Analysis (EDA)
I will explore the cleaned dataset using visual and statistical techniques to uncover hidden patterns, trends, and relationships between variables.