Get introduced to the concept of K-fold cross validation, and understand its implementation in scikit learn with an example.
Learn why feature scaling is important and how to perform it using scikit learn. Also learn about the difference between the two most popular scalers.
Learn the difference between the three types of averages that you can get for f1 score for a multi-class classification problem: weighted, macro and micro.
You’ve heard of train-test split in the context of ML. But what is train-validation-test split? Why is it required, and how to implement it in sklearn? Find out
Learn how to set the custom distance function and the metric params for that function in DBSCAN, for n-dimensional data.