building evaluating - loss function search procedure structure classification performance improvingwith mel frequency cepstral coefficients - classifier buildingfft used classesusing creating - integratinginto site parameterstuning - performanceimproving performancemeasuring slimming training classifierclassy answers tuning classifier performance measuringreceiver operator characteristic (rocused classifier performanceimproving bias-variance high biasfixing high bias or low bias - high variancefixing classy answers classifiertuning classifying instancetuning cloud machine jugrunning on cluster generation automatingwith starcluster - clustering about flat clustering hierarchical clustering kmeans algorithm - test dataobtaining for idea evaluation - cluster package commentcount attribute complex classifiers building complex dataset computer vision confusion matrix usedfor accuracy measurement in multiclass problems - constants package correlation about using - cost function countvectorizer coursera url creationdate attribute cross validated about url cross-validation cross-validationfor regression cross-validation schedule data fetching slimming downto chewable chunks data analysis jugusing for - datamachine learning application cleaning preprocessing reading data sourcesmachine language dimensionality reduction dot(function elastic net model elastic nets usingin scikit-learn ensemble learning enthought python distribution url