Machine learning (ML)
banking, financial services, and insurance sector
cluster analysis
definition
languages, and tools
manufacturing industry
popularity
preparations
principal components
regression vs. classification problems
retail
semi-supervised algorithms
and software engineering
statistics/mathematics
bias–variance trade-off
binomial distribution
correlation and covariance
descriptive vs. inferential statistics
discrete vs. continuous variable
measures of central tendency
normal/Gaussian distribution
numeric vs. categorical data
parameter vs. statistics
Poisson’s distribution
population vs. sample
vector and matrix
steps and process
supervised learning
telecommunication
unsupervised learning algorithm
Mean absolute error (MAE)
Minibatch gradient descent
Multiple linear regression
Multivariate adaptive regression splines (MARS)