Machine Learning Foundations: Statistics
Offered By: LinkedIn Learning
Course Description
Overview
Learn how statistics can help you troubleshoot issues, optimize performance, and innovate, creating new machine learning models that are more efficient.
Syllabus
Introduction
- Foundations of statistics for machine learning
- What you should know
- Defining statistics
- Applications of statistics in ML
- Types of data
- The mean
- The median
- The mode
- The percentile
- The percentage change
- The range
- The variance and the standard deviation
- The standard error of the mean vs. the standard deviation
- The quantiles and box plots
- Missing data
- The correlation
- The covariance
- The correlation coefficient
- The correlation vs. causation
- Introduction to probability distribution
- The uniform distribution
- The normal distribution
- The Bernoulli distribution
- The Multinoulli distribution
- Selection with replacement
- Selection without replacement
- Bootstrapping
- Independent and dependent variables
- Linear regression for continuous values
- Fitting a line
- Linear least squares
- Next steps
Taught by
Terezija Semenski
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