A good start point for Machine Learning is Linear Regression. By studying the Linear Regression algorithm, you will learn:
- Supervised Learning
- Loss Functions
- Loss Functions minimization
- Regularization
These concepts are not exclusive to Linear Regression. They apply to other learning algorithms as well.
By creating and deploying Linear Regression models, you acquire engineering skills that are common to most Machine Learning systems.
Also, you won’t need advanced math to start with Machine Learning nor memorize Machine Learning algorithms details.
Just a brush on Calculus and Linear Algebra will do the job. And most programming languages have Machine Learning libraries that already implemented these algorithms for you.
Therefore, you can focus on the engineering process of cleaning data, feature engineering, model selection, and deployment.
Reinforcement Learning for Fun 