Lab Assignment 3
1)Pick any dataset from the dataset sheet in class sheet and make one prediction model using your imagination with Linear regression. Some examples are:-Predicting weather-Predicting salary according to age You can also pick dataset of your own.
For this task, I have predicted salary based on experience through linear regression.
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2)Implement Kmeans clustering on customers.csv file provided into five clusters.
K-means clustering is a classification method to predict different categories. I have applied this on customers dataset. We have identified the spending score of customers according to their income and divided them into categories.
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3)SVM classification
It is support vector machine, which is a classification technique.
I have applied this technique on a social network ads dataset.
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- Natural Language Processing techniques. Input of the project is one text file. Use the simple approach below to summarize a text file: 1.Read the file 2.Remove all the words like “a the ! ? ...” Which does not have meaning using stopwords in NLTK 3.Using Lemmatization, apply lemmatization on the remaining words 4.Using POS, remove all the verbs 5.Calculate the word frequency of the remaining words 6.Choose top five words that has been repeated most 7.Go through the original text that you had in the file 8.Find all the sentences with those most repeated words 9.Extract those sentences and concatenate 10.Enjoy the summarization
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