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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Acerca de este Curso
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Prueba Coursera para negociosHabilidades que obtendrás
- Regression Analysis
- Supervised Learning
- Linear Regression
- Ridge Regression
- Machine Learning (ML) Algorithms
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Prueba Coursera para negociosOfrecido por
Programa - Qué aprenderás en este curso
Introduction to Supervised Machine Learning and Linear Regression
Data Splits and Polynomial Regression
Cross Validation
Bias Variance Trade off and Regularization Techniques: Ridge, LASSO, and Elastic Net
Reseñas
- 5 stars77,23 %
- 4 stars17,07 %
- 3 stars3,79 %
- 2 stars0,81 %
- 1 star1,08 %
Principales reseñas sobre SUPERVISED MACHINE LEARNING: REGRESSION
Great Course curated by IBM team. It is really designed well and helps to achieve the goal. It is as per the industry standard, and practical. One can do this course thoroughly and get a job.
awesome expirence and iam good to go towards an next course thankyou.
Well structured course. Concepts are explained clearly with hands on exercises.
I recommend this course to everyone who wants to excel in Machine Learning. This is a Great Course!
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