Low-code ML with KNIME: Building Classification Models

Classification models are used to categorize data into a fixed number of discrete classes or categories. The KNIME Analytics Platform allows you to load explore pre-process and use your data to train classification models with little to no code. In this course explore classification models and the metrics used to evaluate their performance. Next construct a KNIME workflow to load and view the data for a classification model. You will clean data impute missing values and cap and floor outlier values in a range. Then you will identify and filter correlated variables and you will convert categorical data to numeric values and express numeric variables. Finally train several different classification models on the training data evaluate them using the test data and select the best model using hyperparameter tuning. Upon completing this course you will have the skills and knowledge to train clean and process your data and to use that data to train classification models and perform hyperparameter tuning.