Machine learning is a branch of computer science in which you can use mathematical input to develop complicated models that fulfil various roles. Python is a popular choice for building machine learning models because of the large number of libraries available. This course will walk you through an astonishing combination of Python and machine learning, teaching you the fundamentals of machine learning so you can construct your own projects. You’ll begin this course by studying Python programming and applying Scikit-Learn to machine learning regression. This lays the groundwork for understanding the theory underpinning simple and multiple linear regression algorithms. Following that, you’ll learn how to solve linear and logistic regression issues. The courses further guides you to harness the power of sklearn, grasping the theory and practical application of logistic regression, and then advances to cover the math underpinning decision trees. Finally, you’ll learn about the various clustering algorithms. By the end of this course, you will be able to use these machine learning algorithms in the real world.