You will get A complete Titanic dataset analysis with EDA, visualizations, and ML model


Project details
I will provide a complete Titanic dataset analysis in Python, designed to be clear, fast, and professional. You will get data cleaning, exploratory data analysis (EDA), and visualizations that highlight survival rates by gender, class, and age. For the Standard and Advanced tiers, I will also include machine learning models such as Logistic Regression and Decision Tree to predict survival outcomes.
My work includes:
A well-documented Jupyter Notebook.
Clean and reproducible Python code (Pandas, Matplotlib, Seaborn, scikit-learn).
PNG visualizations (bar charts, confusion matrix, ROC curve).
A concise summary of key insights.
This project is perfect for anyone who wants a quick, portfolio-ready example of data analysis and machine learning, or needs a reproducible workflow for teaching, demonstrations, or practice.
My work includes:
A well-documented Jupyter Notebook.
Clean and reproducible Python code (Pandas, Matplotlib, Seaborn, scikit-learn).
PNG visualizations (bar charts, confusion matrix, ROC curve).
A concise summary of key insights.
This project is perfect for anyone who wants a quick, portfolio-ready example of data analysis and machine learning, or needs a reproducible workflow for teaching, demonstrations, or practice.
Machine Learning Tools
NumPy, pandas, Python, scikit-learnWhat's included
| Service Tiers |
Starter
$5
|
Standard
$7
|
Advanced
$10
|
|---|---|---|---|
| Delivery Time | 1 day | 1 day | 2 days |
Number of Revisions | 1 | 2 | 2 |
Number of Model Variations | 0 | 1 | 2 |
Number of Scenarios | 1 | 1 | 2 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | - | - |
Source Code |
About Mariam
Machine Learning Engineer
Cairo, Egypt - 12:57 am local time
Steps for completing your project
After purchasing the project, send requirements so Mariam can start the project.
Delivery time starts when Mariam receives requirements from you.
Mariam works on your project following the steps below.
Revisions may occur after the delivery date.
Data Cleaning
Handle missing values, encode categorical features
Exploratory Data Analysis (EDA)
Generate summary stats + charts (gender/class/age survival)



