You will get House Price Prediction using Random Forest | R² ~0.80 | scikit-learn
Project details
Built an end-to-end house price prediction system using Python and
Scikit-learn on the California Housing Dataset (20,000+ samples).
What this project covers:
→ Exploratory Data Analysis with geographic price mapping
→ Feature correlation analysis across 8 housing variables
→ Compared Linear Regression vs Random Forest
→ Random Forest achieved R² of 0.80 — 33% better than baseline
→ Feature importance analysis (Median Income = #1 predictor)
→ Validated with 5-fold cross-validation for reliability
Deliverable: Clean, well-commented Jupyter Notebook with
visualizations, model evaluation, and a reusable predict()
function for new data.
Scikit-learn on the California Housing Dataset (20,000+ samples).
What this project covers:
→ Exploratory Data Analysis with geographic price mapping
→ Feature correlation analysis across 8 housing variables
→ Compared Linear Regression vs Random Forest
→ Random Forest achieved R² of 0.80 — 33% better than baseline
→ Feature importance analysis (Median Income = #1 predictor)
→ Validated with 5-fold cross-validation for reliability
Deliverable: Clean, well-commented Jupyter Notebook with
visualizations, model evaluation, and a reusable predict()
function for new data.
Machine Learning Tools
GitHub Copilot, NumPy, pandas, Python, Python Scikit-Learn, scikit-learnWhat's included $30
These options are included with the project scope.
$30
- Delivery Time 3 days
- Number of Revisions 5
- Number of Graphs/Charts 4
- Model Validation/Testing
- Model Documentation
- Data Source Connectivity
- Source Code
Optional add-ons
You can add these on the next page.
Fast 2 Days Delivery
+$5
Additional Revision
+$5
Additional Model Variation
(+ 1 Day)
+$5About Amaan
Machine Learning Developer | Python | Scikit-learn | Classification |
Islamabad, Pakistan - 5:53 am local time
Learning, with hands-on experience building end-to-end ML solutions
using Python and Scikit-learn.
My professional background gives me something many pure academics
lack: I understand real business problems and how data-driven
solutions actually need to work in practice.
I specialize in:
✅ Regression Models — house price prediction, sales forecasting
✅ Classification Models — spam detection, fraud detection, churn prediction
✅ Clustering — customer segmentation, market basket analysis
✅ NLP — sentiment analysis, text classification
Every project I deliver includes:
→ Clean, well-commented Jupyter Notebooks
→ Exploratory Data Analysis (EDA) with visualizations
→ Model training, evaluation & comparison
→ Clear summary of results and business insights
I take a practical, results-first approach to every project.
No overcomplicating things — just clean code, solid models,
and clear communication throughout.
Whether you need a quick prediction model or a full ML pipeline,
I'd love to help. Message me with your requirements and let's
get started.
🚀 Let's turn your data into decisions.
Steps for completing your project
After purchasing the project, send requirements so Amaan can start the project.
Delivery time starts when Amaan receives requirements from you.
Amaan works on your project following the steps below.
Revisions may occur after the delivery date.
data cleaning, data analysis, data visualization, model building.