Reveal House Sale Price Secrets Using Machine Learning
Embark on an exciting journey into Real Estate with Machine Learning and AI! We'll guide you how to predict house prices, a fundamental task in real estate analytics. You'll gain hands-on expertise using advanced techniques like SHAP (SHapley Additive exPlanations) and Random Forest, empowering you to interpret model results effectively. Whether you're a novice or have some background in data analysis, this project will equip you with the skills needed to excel in your career and confidently apply AI and ML in your job.
4.6 (29 Reviews)

Language
- English
Topic
- Machine Learning
Industries
- Real Estate, Investment
Enrollment Count
- 247
Skills You Will Learn
- Artificial Intelligence, Machine Learning, Python
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- April 1, 2025
A Look at the Project Ahead

In this project, you will wear the hat of a professional real estate analyst and data scientist as you dive into the realm of housing market predictions. Your mission is to create a robust predictive model that can accurately estimate the selling price of houses. But it doesn't stop there; you'll also use the powerful SHAP (SHapley Additive exPlanations) library to dissect your model and identify which factors of the house have the most significant impact on house prices.
- Mastery of Random Forest regression modeling.
- Proficiency in feature engineering and preprocessing.
- Interpretation of SHAP values for model explanation.
- Data visualization and storytelling through interactive dashboards.
- Real-world applications of machine learning in the real estate sector.
- Improved Python programming skills.
- Practical experience in handling and analyzing real-world datasets.
What You'll Need
- Your passion and interest.
- Basic knowledge of Python programming.

Language
- English
Topic
- Machine Learning
Industries
- Real Estate, Investment
Enrollment Count
- 247
Skills You Will Learn
- Artificial Intelligence, Machine Learning, Python
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- April 1, 2025
Instructors
Kang Wang
Data Scientist
I am a Data Scientist in the IBM. I am also a PhD Candidate in the University of Waterloo.
Read moreContributors
Joseph Santarcangelo
Senior Data Scientist at IBM
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.
Read moreWojciech "Victor" Fulmyk
Data Scientist at IBM
As a data scientist at the Ecosystems Skills Network at IBM and a Ph.D. candidate in Economics at the University of Calgary, I bring a wealth of experience in unraveling complex problems through the lens of data. What sets me apart is my ability to seamlessly merge technical expertise with effective communication, translating intricate data findings into actionable insights for stakeholders at all levels. Follow my projects to learn data science principles, machine learning algorithms, and artificial intelligence agent implementations.
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