Lynda Mathematica 11 Machine Learning

/02. Introducing Machine Learning/

02_02-Separate training data from test data.mp4

02_01-Overview of machine learning tasks.mp4

02_03-Import data from a file.mp4

/01. Introduction/

01_02-What you should know.mp4

01_03-Exercise files.mp4

01_01-Welcome.mp4

/03. Preparing Data for Machine Learning/

03_01-Standardize normalize or rescale data.mp4

03_02-Replace values near zero with zero.mp4

03_03-Interpolate data to enter missing values.mp4

03_04-Count values by adherence or nonadherence to a rule.mp4

03_05-Group elements using a rule.mp4

03_06-Sort elements using a rule.mp4

/04. Determining Functions that Generate Data/

04_01-Find a fit using a linear model.mp4

04_02-Find a time series that fits given data.mp4

04_03-Find a formula that represents a data set.mp4

04_04-Find a function that generates a given sequence of values.mp4

/05. Performing Supervised Learning Tasks/

05_01-Calculate the logistic sigmoid function for a data set.mp4

05_02-Classify items using training data.mp4

05_03-Predict values using training data.mp4

05_04-Measure classifier function performance.mp4

05_05-Measure predictor function performance.mp4

05_06-Identify data clusters.mp4

/06. Conclusion/

06_01-Next steps.mp4

/Exercice Files/Chapter01/

HousePriceData.xlsx

/Exercice Files/Chapter02/

CountValues.nb

GroupBy.nb

Interpolate.nb

SortElements.nb

Standardize.nb

Threshold.nb

/Exercice Files/Chapter03/

FindFormula.nb

FindSequence.nb

Linear.nb

TimeSeries.nb

/Exercice Files/Chapter04/

ClassifierPerformance.nb

Classify.nb

Clustering.nb

LogisticSigmoid.nb

Prediction.nb

PredictorPerformance.nb

Total files 40