27:15

HistGradientBoostingClassifier using Scikit-Learn

33:24

Calculate Inception Score (IS) using PyTorch

33:31

RandomizedSearchCV using Scikit-Learn

26:13

GridSearchCV using Scikit-Learn

35:26

K-fold cross validation using Scikit-Learn

24:58

GradientBoostingClassifier using Scikit-Learn

21:21

ExtraTreesClassifier using Scikit-Learn

15:11

Quadratic Discriminant Analysis (QDA) using Scikit-Learn

26:23

CatBoost Classifier | Machine Learning | Python

18:26

Bagging Classifier using Scikit-Learn

28:01

Artificial neural network for regression task using PyTorch

19:22

Hartigan index using Python

19:41

Linear Discriminant Analysis using Scikit-Learn

15:41

XGBoost Classifier | Machine Learning | Python API

20:22

LightGBM Classifier | Machine Learning | Python API

21:53

AdaBoost Classifier using Scikit-Learn

17:19

Logistic Regression using Scikit-Learn

22:10

Complement Naive Bayes using Scikit-Learn

16:15

Gaussian Naive Bayes using Scikit-Learn

16:33

Bernoulli Naive Bayes using Scikit-Learn

20:25

Feature to image representation using Matplotlib

27:36

Multinomial Naive Bayes using Scikit-Learn

27:22

Categorical Naive Bayes using Scikit-Learn

30:02

Random Forest using Scikit-Learn

27:34

Decision Tree using Scikit-Learn

28:57

Support Vector Machine (SVM) using Scikit-Learn

20:43

Train a CNN with data augmentation - Example using Flowers102 dataset

22:22

K-Nearest Neighbors using Scikit-Learn

13:49

Inset plotting using Matplotlib

12:10

Calculate the output shape of convolution, deconvolution and pooling layers in CNN

13:03

Conditional DDPM using PyTorch - Example with MNIST dataset

41:42

Calculate FID (Frechet Inception Distance) using PyTorch

01:20:07

Denoising Diffusion Probabilistic Model (DDPM) using PyTorch - Example with MNIST dataset

58:09

Conditional Variational AutoEncoder (Cond_VAE) - Example using MNIST dataset

48:17

DDPMs - Denoising Diffusion Probabilistic Models

01:03:25

Conditional Generative Adversarial Network (Conditional_GAN) using PyTorch & FashionMNIST dataset

52:58

Deep Convolutional Generative Adversarial Network (DCGAN) using PyTorch and FashionMNIST dataset

51:38

Generative Adversarial Network (GAN) using PyTorch - Example with MNIST dataset

01:11:16

Vector-Quantized Variational AutoEncoder (VQ-VAE) - Example with MNIST dataset

24:58

Eigengap heuristic method to determine the optimal number of clusters

08:57

Push your code from the local (PC) directory to the remote (GitHub) repository using Git

39:23

OpenSlide for Whole-Slide Image (WSI) Processing

19:14

K-Means clustering (using Scikit-Learn)

22:53

Gaussian Mixture Model (GMM) for clustering - calculate AIC/BIC

20:42

OPTICS clustering (using Scikit-Learn)

21:43

DBSCAN clustering (using Scikit-Learn)

25:56

BIRCH clustering - Example with 'titanic' dataset

17:16

Spectral clustering - Example with 'iris' dataset

23:32

Hierarchical clustering - Example with 'wine' dataset

16:05

Create patches from a big image both sequentially and randomly

24:14

Image manipulation using PIL (Python Imaging Library)

25:18

Train a CNN using L1 and L2 regularization

15:09

'random' module in Python

12:15

Basic statistical operations using 'statistics' module in Python

56:10

Classify CIFAR100 images using pretrained EfficientNetV2-L with PyTorch

33:44

Learn to use 'math' module in Python

58:58

Classify SVHN images using pretrained VGG16 with PyTorch

10:49

3 Types of String Formatting in Python

15:03

List Comprehension in Python

33:21

Several operations using strings in Python