Mihai Nica Lectures

Recordings of my Lectures. See also my main channel https://www.youtube.com/@MihaiNicaMath .

Our Zoo of Random Variable and Intro to the Central Limit Theorem | Intro to Probability Fall 2025
Our Zoo of Random Variable and Intro to the Central Limit Theorem | Intro to Probability Fall 2025
From Logistic Regression to Multi-Layer Perceptron on MNIST in JAX | Intro to Data Science M Nov 24
From Logistic Regression to Multi-Layer Perceptron on MNIST in JAX | Intro to Data Science M Nov 24
Предел геометрической функции — экспоненциальная случайная величина | Введение в теорию вероятнос...
Предел геометрической функции — экспоненциальная случайная величина | Введение в теорию вероятнос...
More Poisson random variable, a physical Poisson/Exponential clock, and our random variable zoo
More Poisson random variable, a physical Poisson/Exponential clock, and our random variable zoo
Intro to Neural Networks in JAX | Intro to Data Science F25
Intro to Neural Networks in JAX | Intro to Data Science F25
Limits of the Binomial and Intro to the Poisson distribution | Intro to Probability W Nov 19 F25
Limits of the Binomial and Intro to the Poisson distribution | Intro to Probability W Nov 19 F25
Principle components beyond the first component and some applications | DATA6100 M Nov 17 F25
Principle components beyond the first component and some applications | DATA6100 M Nov 17 F25
Normal approximations to the Binomial Random Variable and Continuity Correction Monday Nov 17 F25
Normal approximations to the Binomial Random Variable and Continuity Correction Monday Nov 17 F25
Approximating Discrete Random Variables by Continuous Random Variables: Uniform RVs. Fri Nov 14 F24
Approximating Discrete Random Variables by Continuous Random Variables: Uniform RVs. Fri Nov 14 F24
Why the lasso eliminates variables and intro to Principle Component Analysis | DATA6100 Nov 12 F25
Why the lasso eliminates variables and intro to Principle Component Analysis | DATA6100 Nov 12 F25
Standardizing random variables, calculating with R, and *why* the normal distribution? Nov 12 F25
Standardizing random variables, calculating with R, and *why* the normal distribution? Nov 12 F25
Intro the Normal (aka Gaussian) Random Variable and Table
Intro the Normal (aka Gaussian) Random Variable and Table
Intro to Ridge Regressions (aka L2 regularization) and cartoon multicollinearity Intro Data Science
Intro to Ridge Regressions (aka L2 regularization) and cartoon multicollinearity Intro Data Science
Practice probability problems: Disk on wood plank, Formulas, Geometric/Binomial, and Multiple Choice
Practice probability problems: Disk on wood plank, Formulas, Geometric/Binomial, and Multiple Choice
When is it better to used biased estimators? Bias variance decomposition, James Stein Nov 3 F25
When is it better to used biased estimators? Bias variance decomposition, James Stein Nov 3 F25
Probability Density vs Mass with a PIPE analagy, and two triangles example STAT1200 Mon Nov 3 F25
Probability Density vs Mass with a PIPE analagy, and two triangles example STAT1200 Mon Nov 3 F25
Introduction to Probability Density Functions and Continuous Random Variables STAT1200 Oct 31 F25
Introduction to Probability Density Functions and Continuous Random Variables STAT1200 Oct 31 F25
Bootstrapping to make trees into random forests | Intro to Data Science W Oct 29 F25
Bootstrapping to make trees into random forests | Intro to Data Science W Oct 29 F25
Expected Value and Variance of the Binomial Distribution | Intro to Probability W Oct 29 F25
Expected Value and Variance of the Binomial Distribution | Intro to Probability W Oct 29 F25
Bayesian Classification, Linear Discriminant Analysis and Naive Bayes DATA6100 Oct 15 F25
Bayesian Classification, Linear Discriminant Analysis and Naive Bayes DATA6100 Oct 15 F25
Multiple hypothesis testing,
Multiple hypothesis testing, "Null Hypothesis Monte Carlo" and The Bootstrap DATA6100 Oct 27 F25
Asymmetric types of classification errors and ROC curves | Intro to Data Science Oct 20 F25
Asymmetric types of classification errors and ROC curves | Intro to Data Science Oct 20 F25
Calculating mean and variance from a list of probabilities | Intro to Probability M Oct 27 F25
Calculating mean and variance from a list of probabilities | Intro to Probability M Oct 27 F25
Eevee introduces the Geometric Random Variable | Intro to Probability F25 Fri Oct 24
Eevee introduces the Geometric Random Variable | Intro to Probability F25 Fri Oct 24
Intro to Random Variables, Probability Mass Function, and Cumulative Distributions WOct15 F25
Intro to Random Variables, Probability Mass Function, and Cumulative Distributions WOct15 F25
More binomial random variable facts and introduction to R STAT1200 M Oct 20 F25
More binomial random variable facts and introduction to R STAT1200 M Oct 20 F25
Calculate binomial probabilities with stattrek and R | Intro to Probability W Oct 22 F25
Calculate binomial probabilities with stattrek and R | Intro to Probability W Oct 22 F25
Intro to the Binomial Distribution and Derivation of its Probability Mass Function FOct17 F25
Intro to the Binomial Distribution and Derivation of its Probability Mass Function FOct17 F25
Multi-class classification, Softmax, Bayesian Classification with 2 Sided Coins DATA6100 W Oct 8 F25
Multi-class classification, Softmax, Bayesian Classification with 2 Sided Coins DATA6100 W Oct 8 F25
Four probability practice problems: 2 step tree problems, Bayes, Rolling triples on 5 dice WOct8F25
Four probability practice problems: 2 step tree problems, Bayes, Rolling triples on 5 dice WOct8F25