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Dlithe-Project

1)Predict whether the cancer is 'benign' or 'malignant' using logistic regression. Compare the results with KNN and Naive Bayes classifier by implementing these as well. The comparison shall be plotted as a table or saved in a file that can be printed back as and when required. Dataset : https://archive.ics.uci.edu/ml/datasets/breast+cancer

  1. Text analytics: web scraping a news article and sentiment analysis. With the help of BeautifulSoup, gather information from a website and use the text data for sentiment analysis. Make use of NLTK and use any classifier to analyze the polarity of the data (Positive, Negative or Neutral). Resource : https://monkeylearn.com/sentiment-analysis/
  1. Clustering Credit Card Users. Dataset : https://www.kaggle.com/arjunbhasin2013/ccdata/

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