Summary of the entire course. The course touches on the basics of Machine Learning and is an excellent starting point for beginners looking to dive into the world of Machine Learning. As a beginner myself with no practical experience in Machine Learning I found the course to be well-explained and reasonably paced.
The course starts out with Supervised Learning. Supervised Learning is basically a way to create an equation based on real world data and results. Once this equation has been created, we can provide new real world data and the equation will tell us the predicted results. This is the simplest form of Machine Learning.
Within Supervised Learning there is Classification which is trying to predict discrete outputs based on the input data. This could be whether it will rain in the next few days. Alternatively, there is Regression which is trying to predict a continuous output based on the input data. For example, predicting students’ test scores based on the amount of sleep they got the previous night. The former uses Logistic Regression while the latter uses Linear Regression. Then there are neural networks which can be thought of as multiple small equations fit into a larger equation.
On the other side of the coin, Unsupervised Learning begins in Week 8. This is basically training an equation to provide us with…
