- Machine Learning = Function Optimization
- y = f(x)
- A map: y = f(x) for some x
- A function: y = f(x) for every x
- A function is a table of values
- A function is a graph
- Functions convert information from one type to another
- y = a result
- x = a data sample
- Functions have many shapes
- linear
- polynomial
- exp/log
- ... more!
- Machine Learning = Derivative Computation
- dy/dx(f(x))
- Where the derivative changes direction is an optimum
- Optima
- Either the place where the answer is or:
- The place where you are stuck on the wrong answer
Start with the LSMLMBC github assignment: https://github.com/LambdaSchool/ML-Precourse. The rest of the information you need will be delivered tomorrow. Send a pull request with your completed assignment after the lesson tomorrow.