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Project
Part A: Clustering
Find a dataset in kaggle or any other source. Make sure that each dataset is at least 500 MB.Write a detailed description of the dataset.Preprocess the dataset.Using K-means algorithm to cluster the dataset.Use the Elbow method and the Silhouette method to find the optimal K.
Part B: Regression
Find one or two datasets in kaggle or any other source. Make sure that each dataset is at least 500 MB.Write a detailed description of each dataset.Preprocess each dataset.Divide each dataset into training and testing.Build two regression models.Test the models and compute their accuracy.
Part C: Classification
Find one or two datasets in kaggle or any other source. Make sure that each dataset is at least one 500MB.Write a detailed description of each dataset.Preprocess each dataset.Divide each dataset into training and testing.Build two classification models.Test the models and compute their accuracy.
Describe and estimate the number of scenarios that must be managed and decide how many are easy, normal, and difficult, and why.
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