Statistical hypothesis testing, types of errors, and interpretation of p values
Learn how to propose null and alternate hypotheses, perform the statistical analysis, and interpret the results
Learn how to propose null and alternate hypotheses, perform the statistical analysis, and interpret the results
Learn how to query pandas DataFrame to select rows based on exact match, partial match, and conditional match in pandas DataFrame
learn how to import CSV, Excel, Tab, JSON, and SQL files in pandas for data analysis and visualization
NaN
) in pandas
Analyse and handle null or missing values in pandas series and dataframe
learn to join pandas dataframes in multiple ways
Learn how to use probability distributions, probability mass function (PMF), cumulative distribution function (CDF), and probability density function (PDF)
Logistic regression for prediction of breast cancer, assumptions, feature selection, model fitting, model accuracy, and interpretation
Implementation of Support vector machine (SVM) in Python for prediction of heart disease. Learn SVM basics, model fitting, model accuracy, and interpretation
pyplot.scatter
)
Learn how to create 2D and 3D scatter plots from numerical arrays and pandas DataFrame using Python matplotlib package
Multicollinearity refers to the significant correlation among the independent variables in the regression model. Variance Inflation Factor (VIF) helps to dia...
Multiple regression analysis using statsmodels. Learn how to define regression model, assumptions, metrics evaluation, and interpretation
Linear regression using PyTorch