A rigorous and engaging deep-dive into statistics and machine-learning, with hands-on applications in Python and MATLAB.
InstructorMike X CohenThe curriculum covers essential prerequisites like summation notation and the logistic function, progressing into advanced topics such as ANOVA, GLM/Regression, and non-parametric tests.
Lessons provide implementation paths for both Python and MATLAB/Octave, covering essential tasks like central tendency and t-tests.
One signal suggests that code snippets can lack thorough explanation, occasionally requiring external research to understand specific functions. Note that these signals were provided in reviews predating the displayed update date; while an update is noted, it does not prove a correction has been made.
One signal suggests that code snippets can lack thorough explanation, occasionally requiring external research to understand specific functions. Note that these signals were provided in reviews predating the displayed update date; while an update is noted, it does not prove a correction has been made.
The curriculum aligns well with the stated goals of teaching statistics and machine learning via code.