The ML and its automation journey are long. The aim of this chapter was to familiarize ourselves with machine learning concepts; most importantly, the scikit-learn and other Python packages, so that we can smoothly accelerate our learning in the next chapters, create a linear regression model and six classification models, and learn about clustering techniques and compare the models with each other.
We used a single HR attrition dataset for creating all classifiers. We observed that there are many similarities in these codes. The libraries imported are all similar except the one used to instantiate the machine learning class. The data preprocessing module is redundant in all code. The machine learning technique changes based on the task and data of the target attribute. Also, the evaluation methodology is equivalent to the similar type of ML methods.
Do you think that...
