Much more detailed descriptions are present in the actual ipynbs;
#hw1: Build a decision tree classifier with the scikit library function calls to predict whether a data scientist candidate is going to look for a new job or will work for the company - target column is the target variable.
#hw2: work on a dataset from SIDER Side Effect Resource. SIDER contains information on marketed drugs and their recorded adverse drug reactions (ADR). This dataset simply contains entries of drugs and their potential side effects. Analyze data and calculate conditional probability of a side efefct if we know another side effect is present.
#hw3: After establishing the tasks introduced in the Data Preprocessing, the dataset is almost ready to be applied to machine learning models. We are interested in predicting the decision of the participants' to continue dating the assigned partner using Random Forest.