bike sharing dataset (cont outliers - preprocessing - linear regression - modeling (see modelingbike sharing datasetproblem statement regression analysis assumptions cross validation normality test - residual analysis -squared types binary classification model bin-counting scheme bing liu' lexicon binning image intensity distribution boosting methods botsee web crawler box-cox transform - box plots - building machine intelligence calinski-harabaz index - candidate model canny edge detector categorical data encoding features bin-counting scheme dummy coding scheme effect coding scheme one hot encoding scheme feature hashing scheme nominal - ordinal - categorical variables channel pixels - chi-square test - classification models binary classification confusion matrix accuracy score precision - structure - test dataset handwritten digit - multi-class classification output formats clustering methods clustering models calinski-harabaz index - completeness density based distance between data points evaluation hierarchical - homogeneity partition based - sc -measure clustering strategy data cleaning cluster analysis - customerid field data preprocessing - frequency and monetary value - -means clustering - recency - separate transactionsgeographical region rfm modelcustomer value clustering vs customer segmentation comma separated values (csvdataframe - dict pandas reader function sample file computationtheory of computer science (csalgorithms code data structures defined practical programming languages theoretical conditional probability confusion matrix accuracy score precision - structure - test dataset content-based recommendation engines convolutional neural networks (cnnsarchitecture artistic style transfer (see artistic style transfercnnscomponents - feature map visualizations - image classification dataset deep learning classifierpretrained models - deep learning classifierscratch - problem statement