Free Machine Learning Courses from IBM

If you are interested in Machine Learning, these FREE courses from IBM make learning easy and accessible for everyone

1. Supervised Machine Learning: Regression. In this course you are going to learn about:

* Differentiate uses and applications of classification and regression in the context of supervised machine learning 

* Describe and use linear regression models

* Use a variety of error metrics to compare and select a linear regression model that best suits your data

* Articulate why regularization may help prevent overfitting

* Use regularization regressions: Ridge, LASSO, and Elastic net

2. Supervised Machine Learning: Classification. In this course you are going to learn about:

Differentiate uses and applications of classification and classification ensembles

* Describe and use logistic regression models

* Describe and use decision tree and tree-ensemble models

* Describe and use other ensemble methods for classification

* Use a variety of error metrics to compare and select the classification model that best suits your data

* Use oversampling and undersampling as techniques to handle unbalanced classes in a data set

3. Unsupervised Machine Learning. In this course you are going to learn about:

* Explain the kinds of problems suitable for Unsupervised Learning approaches

* Explain the curse of dimensionality, and how it makes clustering difficult with many features

* Describe and use common clustering and dimensionality-reduction algorithms

* Try clustering points where appropriate, compare the performance of per-cluster models

* Understand metrics relevant for characterizing clusters

What would you like to learn next?

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