22 тысяч подписчиков
170 видео
Understanding derivatives - the basics
Support Vector Machines (SVM) - the basics | simply explained
Artificial neural networks (ANN) - explained super simple
Logistic regression : the basics - simply explained
Linear regression | the R-squared value
K nearest neighbors (KNN) - explained | validation
Assumptions in Linear Regression - explained | residual analysis
Validation techniques - explained with simple examples (Hold-out, cross-validation, LOOCV)
Paired vs unpaired t-test
Bootstrap confidence intervals - explained
Deep learning - explained simply | Early Stopping & Dropout
How do AI and neural networks work?
Autoencoders - simply explained
Multiple linear regression - explained with two simple examples
How to check normal distribution | The normality assumption
Why we divide by n-1 when calculating the sample variance – the proof | unbiased estimator
Odds vs Probability - explained
Convolutional Neural Network (CNN) – explained simply
Stochastic gradient descent (SGD) vs mini-batch GD | iterations vs epochs - Explained
Standard deviation | how to calculate the SD and variance
Receptor ligand kinetics | mathematical modeling
SPSS for beginners in 22 minutes - enter data, plot and t-test
PCA : the basics - explained super simple
Meta-analysis | The inverse variance method | Forest plot in R
Neural networks with continuous output | ANN vs Regression
PCA : the math - step-by-step with a simple example
Logistic regression : how to use it as a classifier
Forward and backward selection and best subset selection
Comparing Kaplan-Meier curves - the Log-rank test
Post hoc test | Bonferroni - explained
Familywise error rate (FWER) - explained
Missing Data Imputation: Mean, Median & KNN Explained
The SIR model | the math of epidemics - explained with a simple example
Post hoc test | Fisher's LSD – explained
The Mantel-Haenszel method - clearly explained | deal with confounding
The standard error of the mean (SEM)| how to calculate and interpret | SE vs SD
Recurrent neural network (RNN) - explained super simple
Understanding exponential growth | discrete vs continuous growth
Relative risk - how to calculate and interpret | 95% CI
PCA : standardization and how to extract components
The weighted mean - explained
Expected value vs mean
Multinomial logistic regression | softmax regression | explained
Image classification with machine learning - explained | CNN ANN Logistic regression Decision trees
Lasso regression - explained
Bayesian statistics - the basics
Statistical power - Parametric vs Nonparametric test
How to identify and deal with outliers | The 1.5 IQR rule | Boxplots
Linear regression | hypothesis testing
Nonlinear mixed effects models (NLME) - explained
