1)Pick any dataset from the dataset sheet in class sheet and make one prediction model using your imagination with Linear regression.

Task#1_SourceCode

2) Implement Kmeans clustering on customers.csv file provided into five clusters.

Task#2_SourceCode

Implement SVM classification,

1)Choose one of the dataset using the datasets features in the scikit-learn(you should not select the same dataset in the class) 2)Load the dataset 3)According to your dataset, split the data to 20% testing data, 80% training data(you can also use any other number) 4)Fit the model on the training data 5)First apply linear kernel 6)Apply the accuracy 7)Then apply RBF kernel instead of linear 8)Report your view if changing the kernel affect the accuracy of your model ##

Task#3_SourceCode

4)Write a program Take Input of the project isone text file. Use the simple approach below to summarize a text file:-Read the file-Using Lemmatization, apply lemmatization on the remaining words-Using POS, remove all the verbs-Calculate the word frequency of the remaining words-Choose top five words that has been repeated most-Go through the original text that you had in the file-Find all the sentences with those most repeated words-Extract those sentences and concatenate-Enjoy the summarization

Task#4_SourceCode