Week 7 CST 383
This week in CST 383 we focused on the last few concepts of the course which were managing how to encode categorical data in order to feed it to SciKit-Learning models and related methods, then we went over logistic regression which despite its name is actually a way to solve classification problems in regards to categorical binaries, and lastly we discussed the different ways we can overfit a machine learning model and how to fix it. In this case, overfitting means the model performs extremely well on the training data, but fails to generalize to new unseen data such as a test set or future observations. The homework this week was an overarching highlight of everything we had learned in this course though mainly the concepts that we had learned in the previous three weeks from exploring machine learning. It was interesting to see how I can challenge myself to identify how to pre-process data by encoding categorical variables, identifying when to split and scale data, testing different...