This machine learning cheat sheet gives you a visual overview of 6 must-know machine learning algorithms (and where to learn more).
- Linear Regression: train your linear model to predict output values.
- K-Means Clustering: apply it on unlabeled data to find clusters and patterns in your data.
- K-Nearest Neighbors: use a similarity metric to find the k closest data points to a certain input point. The training phase is as simple as storing the data points in your model. Only the inference phase is relatively expensive.
- Support Vector Machines: Find the best decision boundary that best separates your data classes for classification problems.
- Decision Tree Classification: Train your model one feature at a time—decision trees are very useful because humans can understand them.
- Multilayer Perceptron: The most simple case of a neural network for maximum learning power.
Here’s the cheat sheet that not only gives you a quick overview but also provides you links to more in-depth tutorials. Print it, check out one tutorial per day, and cross it off with a fat “X” to set your machine learning foundation now!
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