Extract three archival data sets from a reputable data repository, such as Kaggle or UCI machine learning data repository. Each of the dataset should be in relation to classification $($target or dependent variable is discrete$),$ regression $($target is continuous$),$ and clustering $($no target$).$

The following tasks are expected to be addressed by each group:

$1.$ Describe each dataset wrt the data source, features, missing values, etc.

$2.$ Discuss what kind of problem$($s$)$ each of the dataset can be used to address.

$3.$ Discuss how you will preprocess each dataset. Justify, based on literature, the preprocessing techniques that will be considered.

$4.$ For each of the data set, which machine learning technique$($s$)$ will be used to setup the prediction or clustering models. Justify, based on literature, the machine learning techniques that will be considered.

$5.$ Discuss how you will go about the training, validation and testing for each dataset.

$6.$ Prepare a PowerPoint presentation summary for this assignment and note that you will be presenting it during class session.