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1. Why Machine Learning Matters

2.1: Supervised Learning

Supervised learning identifies patterns in data and learns heuristics by running labeled training data through an algorithim (or a bunch of them). Then we can use it to estimate the values/classifications of unlabelled data.

Regression methods are used to predict numbers, for example given age, sex, weight, etc etc estimate the height of a person.

• Simple linear regression works for smaller data, and gradient descent for larger

Be wary of underfitting and overfitting:

2.2 Supervised Learning II

Predict what something is using logistic regression or SVM, for example what kind of fruit.

• Logistic regression applies a sigmoid function after a linear regression to output a probability b/w 0 and 1.