Instructions System hardware and OS: Windows Server 2016 Datacenter Processor: Intel(R) Xeon(R) CPU E5-2673 v4 @ 2.30Ghz 2.29 GHz RAM: 32.0 GB System type: 64-bit operating system, x64-based processor Anaconda version: Anaconda2 5.0.0 64-bit Python version: Python 3.5.4 Packages requirement numpy == 1.15.4 pandas == 0.20.3 matplotlib == 2.1.0 csv == 1.0 os time sklearn == 0.20.2 pickle imblearn == 0.4.3 Dataset Problem 1: Bank Marketing Data Set (bank.csv) Original URL: https://archive.ics.uci.edu/ml/datasets/Bank+Marketing my GitHub repository: https://github.com/LUSAQX/Assignment1/tree/master/Data training dataset: https://github.com/LUSAQX/Assignment1/blob/master/Data/train_test_split/trainset_p1.csv test dataset: https://github.com/LUSAQX/Assignment1/blob/master/Data/train_test_split/testset_p1.csv training feature set after resampling: https://github.com/LUSAQX/Assignment1/blob/master/Data/train_test_split/X_train_smote_p1.csv training target class after resampling: https://github.com/LUSAQX/Assignment1/blob/master/Data/train_test_split/y_train_smote_p1.csv Problem 2: Large Movie Review Dataset (aclImdb) Original URL: http://ai.stanford.edu/~amaas/data/sentiment/ training dataset: https://github.com/LUSAQX/Assignment1/blob/master/Data/train_test_split/trainset_p2.csv test dataset: https://github.com/LUSAQX/Assignment1/blob/master/Data/train_test_split/testset_p2.csv Code Problem 1: https://github.com/LUSAQX/Assignment1/blob/master/Code/Problem_1.ipynb Problem 2: https://github.com/LUSAQX/Assignment1/blob/master/Code/Problem_2.ipynb, https://github.com/LUSAQX/Assignment1/blob/master/Code/Problem_2(Neural%20Net).ipynb