Welcome. You are in the right place if you are just starting your journey learning Machine Learning. I found my very old notes / cheat sheet about Supervised Machine Learning for beginners when I started learning ML a long time ago. Here is the link to a high resolution pdf if you are interested.
A little primer to Supervised Machine Learning follows. Read my attached original notes for details
| Supervised Learning is a field of Machine Learning that learns from examples / known outputs y and is then able to predict y from other newer values of x | |
| Linear Regression | Classification |
| Algo predicts an output value y from infinite possible values for a given input x | Definition : Algo predicts finite outputs / categories for a given input |
| Model function : f(x) = wx +b Is basically a function for straight line | Model function for Logistic Regression : f(x) = g(z) = 1/ (1 + e-z ) Is a function describing a sigmoid |
 Graph of the function |  Graph of Sigmoid function |
 Convex plot of Cost function | |
Now that you have notes on Supervised Machine Learning for beginners, other foundational ML topic you may be interested in is Null and Alternate Hypothesis. Happy reading !
