Aladdin Persson Courses

NeRFs- Neural Radiance Fields - Paper Explained

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Explore neural radiance fields for 3D scene representation and view synthesis, covering network architecture, key concepts, learning process, and advanced techniques.

• YouTube
• 20 minutes
• On-Demand
• Free Video

Graph Neural Networks- A Gentle Introduction

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Gentle introduction to Graph Neural Networks, covering key concepts, properties, and variants. Learn about graph representation, information propagation, and common tasks in this emerging field of machine learning.

• YouTube
• 29 minutes
• On-Demand
• Free Video

StyleGAN Paper Explained

Comprehensive explanation of StyleGAN paper, covering architecture, image quality techniques, style properties, mixing, disentanglement, and training details for advanced AI image generation.

• YouTube
• 41 minutes
• On-Demand
• Free Video

Pix2Pix Implementation From Scratch

Learn to implement Pix2Pix from scratch, covering discriminator and generator models, dataset loading, and training. Gain hands-on experience in building this powerful image-to-image translation algorithm.

• YouTube
• 1 hour 2 minutes
• On-Demand
• Free Video

YOLOv3 From Scratch

Comprehensive tutorial on implementing YOLOv3 object detection algorithm from scratch using PyTorch, covering architecture, dataset loading, loss function, and training setup.

• YouTube
• 1 hour 52 minutes
• On-Demand
• Free Video

EfficientNet Paper Walkthrough

Comprehensive walkthrough of the EfficientNet paper, exploring model scaling, proposed methods, and results. Offers insights into innovative approaches for improving neural network efficiency.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Building Our First Simple GAN

Learn to build a simple Generative Adversarial Network (GAN) using fully connected layers and train it on the MNIST dataset. Explore the architecture, setup, and training process for this fundamental deep learning model.

• YouTube
• 24 minutes
• On-Demand
• Free Video

TensorFlow Tutorial - Custom Dataset for Images

Learn efficient methods to load custom image datasets in TensorFlow using structured subfolders, CSV annotations, or single folders. Covers image_dataset_from_directory, ImageDataGenerator, and more.

• YouTube
• 25 minutes
• On-Demand
• Free Video

TensorFlow Tutorial - Neural Networks with Sequential and Functional API

Learn to build neural networks in TensorFlow 2.0 using Keras Sequential and Functional API. Covers model creation, layer feature extraction, and model summaries with hands-on MNIST dataset examples.

• YouTube
• 21 minutes
• On-Demand
• Free Video

TensorFlow Tutorial - Tensor Basics

Comprehensive guide to essential tensor operations in TensorFlow 2.0, covering initialization, casting, math operations, indexing, and reshaping. Builds foundation for neural network development.

• YouTube
• 21 minutes
• On-Demand
• Free Video

How to Learn Deep Learning - The Most Efficient Way to Go From Beginner to Advanced

Comprehensive guide to efficiently learn deep learning, from prerequisites to advanced topics. Covers recommended courses, resources, and practical advice for beginners to progress to an advanced level.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Pytorch Image Captioning Tutorial

Learn to build an image captioning system from scratch using PyTorch, covering CNN and RNN implementation, training setup, and evaluation on the Flickr8k dataset.

• YouTube
• 36 minutes
• On-Demand
• Free Video

Pytorch Neural Style Transfer Tutorial

Learn to implement Neural Style Transfer from scratch in PyTorch, covering theory and practical coding to blend content and style images for artistic results.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Complete Pytorch Tensor Tutorial - Initializing Tensors, Math, Indexing, Reshaping

Comprehensive tutorial on PyTorch tensors covering initialization, math operations, indexing, and reshaping. Essential foundation for deep learning with practical examples and useful operations.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Pytorch DCGAN Tutorial

Implement a DCGAN in PyTorch to generate new MNIST digits. Learn GAN fundamentals, architecture, and training techniques through hands-on coding and visualization.

• YouTube
• 40 minutes
• On-Demand
• Free Video