Aladdin Persson Courses

ProGAN Implementation From Scratch

Learn to implement ProGAN from scratch, covering model architecture, training setup, and evaluation. Gain hands-on experience in advanced generative adversarial network techniques.

• YouTube
• 1 hour 29 minutes
• Self-Paced
• Free Video

ProGAN Paper Walkthrough

Detailed walkthrough of the ProGAN paper, covering progressive growing, MiniBatch Std, layer fading, normalization techniques, and implementation details for advanced GAN enthusiasts.

• YouTube
• 32 minutes
• Self-Paced
• Free Video

CycleGAN Implementation From Scratch

Learn to implement CycleGAN from scratch, covering discriminator, generator, dataset preparation, and training process for image-to-image translation tasks.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

EfficientNet From Scratch in Pytorch

Learn to implement EfficientNet from scratch using PyTorch, covering key concepts like CNNBlock, SqueezeExcitation, and InvertedResidualBlock with stochastic depth.

• YouTube
• 39 minutes
• Self-Paced
• Free Video

How to Solve Santander Kaggle Transaction Competition - Top 1% Solution, No Ensemble

Learn to achieve top 1% in Santander Kaggle competition using neural networks, feature engineering, and data analysis techniques. Improve your machine learning skills with practical insights and strategies.

• YouTube
• 58 minutes
• Self-Paced
• Free Video

PyTorch Image Segmentation Tutorial with U-NET - Everything From Scratch

Learn to implement U-NET for image segmentation from scratch, covering model architecture, dataset preparation, training process, and evaluation techniques in PyTorch.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

Albumentations Tutorial for Data Augmentation - PyTorch Focused

Learn data augmentation techniques using Albumentations library for image classification, segmentation, and object detection tasks, with a focus on PyTorch implementation and practical examples.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

WGAN Implementation From Scratch With Gradient Penalty

Implement WGAN and WGAN-GP in PyTorch, focusing on improving GAN training stability through loss function modifications. Includes theoretical explanations and practical coding.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

DCGAN Implementation From Scratch

Learn to implement DCGAN from scratch, focusing on convolutional neural networks for image generation. Covers discriminator and generator implementation, weight initialization, and training on MNIST and CelebA datasets.

• YouTube
• 36 minutes
• Self-Paced
• Free Video

YOLOv1 from Scratch

Comprehensive tutorial on implementing YOLOv1 from scratch, covering architecture, loss function, dataset preparation, training, and evaluation for object detection.

• YouTube
• 1 hour 43 minutes
• Self-Paced
• Free Video

Classifying Skin Cancer - TensorFlow Tutorial

Build a TensorFlow model to classify skin lesions as benign or malignant. Learn preprocessing, model setup, training, and evaluation using metrics like ROC curves for this important medical application.

• YouTube
• 31 minutes
• Self-Paced
• Free Video

TensorFlow Tutorial - Custom Dataset for Text with TextLineDataset

Learn to create custom text datasets in TensorFlow using TextLineDataset. Covers loading, filtering, vocabulary creation, and numericalizing for various text data structures, including IMDB reviews and translation datasets.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Complete TensorBoard Guide

Comprehensive guide to TensorBoard features including loss plots, image visualization, confusion matrices, hyperparameter tuning, embedding projections, and TensorFlow profiler for model optimization and analysis.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

TensorFlow Tutorial - TensorFlow Datasets

Learn to use TensorFlow Datasets for loading, preprocessing, and modeling image and text data. Covers MNIST image classification and IMDB sentiment analysis with practical examples and code demonstrations.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

How to Build Custom Datasets for Text in PyTorch

Learn to build custom datasets for text in PyTorch, focusing on image captioning with the Flickr8k dataset. Covers dataset creation, vocabulary setup, batch padding, and data loading for various NLP tasks.

• YouTube
• 35 minutes
• Self-Paced
• Free Video