Deadline is 23 july evening.Your task is to rank/filter/process/adjust features in the dataset and run one or more ML algorithms to predict a class(the class depends upon the dataset).

Deadline 23 july evening Project 1 Choose a dataset from publicly available datasets such as: UCI - Machine learning Repository: [login to view URL] [login to view URL] [login to view URL] [login to view URL] [login to view URL] KAGGLE [login to view URL] WORLD BANK [login to view URL] The selected dataset must be at least order of 10,000 instances. Your task is to rank/filter/process/adjust features in the dataset and run one or more ML algorithms to predict a class (the class depends upon the dataset). It is preferable not to use WEKA, scikit-learn or other tools more suitable for large datasets. A good project should include: • description of the dataset and of the ML task • analysis and filtering of features, • description of the algorithms used • comparison of experiments, • final comments on performance metrics.