Predictions: Regression for Car Mileage and Diamond Price
Master essential skills for mind-blowing forecasts and unlock a world of data-driven success. In this project, you'll discover how to build powerful machine learning regressors to predict Car Mileage and Diamond Values. Gain in-demand skills for success and make informed decisions in industries such as automotive and jewelry by harnessing the potential of data-driven predictions.
4.6 (410 Reviews)

Language
- English
Topic
- Data Science
Enrollment Count
- 1.72K
Skills You Will Learn
- Artificial Intelligence, Machine Learning, Python, Pandas, Data Science
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- April 27, 2025
A Look at the Project Ahead
- Dataset Preparation:
- As a first step, you will gather datasets of car mileage and diamond samples.
- Feature Selection:
- Identify relevant features from the dataset that are informative for regression models.
- Model Training and Evaluation
- This stage involves training your selected model using the dataset and evaluating your model performance.
What You'll Need

Language
- English
Topic
- Data Science
Enrollment Count
- 1.72K
Skills You Will Learn
- Artificial Intelligence, Machine Learning, Python, Pandas, Data Science
Offered By
- IBMSkillsNetwork
Estimated Effort
- 30 minutes
Platform
- SkillsNetwork
Last Update
- April 27, 2025
Instructors
Ramesh Sannareddy
Corporate IT Trainer
Ramesh Sannareddy holds a Bachelors Degree in Information Systems (Birla Institute of Technology, Pilani). He has two and a half decades of experience in Information Technology Infrastructure Management, Database Administration, Information Integration and Automation. He worked for companies like Intergraph, Genpact, HCL, and Microsoft. Currently, he is a freelancer and pursues his passion for teaching. He teaches Data Science, Machine Learning, Programming and Databases.
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Vicky Kuo
Data Scientist
I believe that success isn't just about individual milestones, but also about uplifting and encouraging others to reach their potential. This is why I'm passionate about combining my technical background with my eagerness to help people overcome technological hurdles and accelerate growth. When I’m not on the job, I love hiking with my two dogs or relaxing in a coffee shop. There's nothing better than having an insightful conversation over coffee, or even better, some volunteer work! Please feel free to reach out to me on LinkedIn.
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