Coursera-Supervised Machine Learning: Regression and Classification-Learning note Part1

Supervised machine learning model:

• Regression: 
• Image some data point is a known correct data, and given a new data to predict estimate value.
• Simplied is linear model, f(x) = ax + b, and set b to zero, so we can caculate the standard error from actual data with estimated data.
• So the standard error, or called cost function formula, can estimate the difference of changing a to standard error.
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