Unsupervised ML
In this course, you will learn how to train Machine Learning models to make predictions, both numerical (regression) and categorical (classification). These include linear models, probabilistic models, and neural networks.
You will learn how to evaluate these models, and improve them, in order to best fit your data.
There are video lectures and code labs, so you can apply what you’ve learned!
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Chapter 1 - Linear Models
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Hard Clustering: K-means and Hierarchical
Clustering
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The Covariance Matrix
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Soft Clustering: Gaussian Mixture Models
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Chapter 2 - Dimensionality Reduction
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