This course introduces you to one of the main types of modelling families of supervised Machine Learning: Regression. You will learn how to train regression models to predict continuous outcomes and how to use error metrics to compare across different models. This course also walks you through best practices, including train and test splits, and regularization techniques.
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About this Course
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Shareable Certificate
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Intermediate Level
Approx. 20 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessSkills you will gain
- Regression Analysis
- Supervised Learning
- Linear Regression
- Ridge Regression
- Machine Learning (ML) Algorithms
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level
Approx. 20 hours to complete
English
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
4 hours to complete
Introduction to Supervised Machine Learning and Linear Regression
4 hours to complete
11 videos (Total 72 min), 2 readings, 5 quizzes
4 hours to complete
Data Splits and Polynomial Regression
4 hours to complete
7 videos (Total 56 min), 1 reading, 5 quizzes
4 hours to complete
Cross Validation
4 hours to complete
7 videos (Total 63 min), 1 reading, 4 quizzes
3 hours to complete
Bias Variance Trade off and Regularization Techniques: Ridge, LASSO, and Elastic Net
3 hours to complete
11 videos (Total 87 min), 1 reading, 4 quizzes
Reviews
- 5 stars77.44%
- 4 stars16.84%
- 3 stars3.80%
- 2 stars0.81%
- 1 star1.08%
TOP REVIEWS FROM SUPERVISED MACHINE LEARNING: REGRESSION
by MKNov 8, 2021
Thank you Coursera.
Thank you IBM.
Thank you to all intructors.
by PBJun 15, 2021
Great way learn about machine learning development of regression models
by NADec 27, 2020
Learned really about supervised learning and more importantly regularization and some available methods.
by SPAug 10, 2021
Well structured course. Concepts are explained clearly with hands on exercises.
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