![]() ![]() How to optimize the efficiency of the regression model?.How to evaluate the model for a regression problem?.How to train the model in a regression problem?.Introduction to classification problems, Identification of a regression problem, dependent and independent variables.Introduction to scikit-learn, Keras, etc.Linear Regression, Logistic Regression, Error in regression, Information Gain using RegressionĬlassification problem using excel on sales data, and statistical tests on various samples from the population. ![]() Inferential Statistics, Hypothesis Testing, ANOVA, Covariance, Correlation.Standardization, Normalization, Probability Distributions.Binary Classification Problems, Confusion Matrix, AUC, and ROC curve.Power Pivot, Power Query, and Power View.Multiples: A set of charts with the same axes, Matrices, Cards, Tiles.Bar charts, Column charts, Line charts, Maps.Charts, Pie charts, Scatter and bubble charts.Handling Text Data, Splitting, combining, data imputation on text data, Working with Dates in Excel, Data Conversion, Handling Missing Values, Data Cleaning, Working with Tables in Excel, etc.VBA Macros, Ranges, and Worksheet in VBA.Working with Charts in Excel, Pivot Table, Dashboards, Data And File Security.Reading the Data, Referencing in formulas, Name Range, Logical Functions, Conditional Formatting, Advanced Validation, Dynamic Tables in Excel, Sorting and Filtering.Other options available in the PROC TRANSPOSE statement that can be found in the SAS Help Guide. The resulting dataset will have one row for each variable identified in the VAR statement. For wide-to-long datasets, there are usually multiple variables in the VAR statement.For long-to-wide datasets, there is usually one variable in the VAR statement.These are the values that will appear in the cells of the transposed variables. The VAR statement is where you actually tell SAS what variables you want transposed. ![]() However, if you do supply an ID variable, it will determine the column structure.
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