Bayesian Optimization
8:15
4.221
Bayesian Optimization
The Rbf Kernel
4:22
1.520
The Rbf Kernel
The Kernel Trick
9:03
7.376
The Kernel Trick
The Curse Of Dimensionality
8:07
5.347
The Curse Of Dimensionality
Cross-Entropy - Explained
4:27
2.896
Cross-Entropy - Explained
Weights Initialization In Neural Networks
4:13
1.592
Weights Initialization In Neural Networks
Dropout Regularization - Explained
3:59
1.520
Dropout Regularization - Explained
L1 Vs L2 Regularization
4:04
7.971
L1 Vs L2 Regularization
Cross-Entropy - Explained
4:27
2.896
Cross-Entropy - Explained
Why We Perform Feature Normalization In Ml
5:32
2.792
Why We Perform Feature Normalization In Ml
The Curse Of Dimensionality
8:07
5.347
The Curse Of Dimensionality
Gradient Boosting With Regression Trees Explained
4:09
16.623
Gradient Boosting With Regression Trees Explained
Least Squares Vs Maximum Likelihood
4:49
22.525
Least Squares Vs Maximum Likelihood
T-Test Explained
9:12
7.174
T-Test Explained
Dropout Regularization - Explained
3:59
1.520
Dropout Regularization - Explained
The Kernel Trick
9:03
7.376
The Kernel Trick
Fourier Transform Formula Explained
10:15
10.782
Fourier Transform Formula Explained
Covariance And Correlation Explained
4:36
12.729
Covariance And Correlation Explained
Transformer Self-Attention Mechanism Visualized
9:29
3.605
Transformer Self-Attention Mechanism Visualized
Covariance Matrix - Explained
3:33
11.428
Covariance Matrix - Explained
Confidence Intervals Explained
4:24
2.272
Confidence Intervals Explained
Linear Regression Vs Maximum Likelihood
0:54
24.996
Linear Regression Vs Maximum Likelihood
Singular Value Decomposition Svd Explained
5:40
6.564
Singular Value Decomposition Svd Explained
Xgboost Explained
0:48
41.351
Xgboost Explained
Basic Probability Distributions Explained Bernoulli, Binomial, Categorical, Multinomial
8:01
1.500
Basic Probability Distributions Explained Bernoulli, Binomial, Categorical,...