Grasp Superior Statistics, Deep Studying Optimization, Time Collection Forecasting, Bayesian Modeling
What you’ll be taught
Perceive and apply key chance distributions, together with Regular, Binomial, and Poisson distributions.
Remodel skewed datasets into regular distributions utilizing methods like log, sq. root, and energy transformations.
Calculate and interpret confidence intervals for vital statistical estimates, akin to mannequin accuracy.
Distinguish between inhabitants information and pattern information, and perceive their roles in evaluation.
Carry out random sampling accurately and perceive its impression on the validity of information evaluation.
Consider classification fashions utilizing metrics like accuracy, precision, recall, and F1 rating.
Establish and handle underfitting and overfitting points in machine studying and statistical modeling.
Apply statistical modeling ideas to real-world deep studying workflows.
English
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