Aladdin Persson Courses

Variational Autoencoder Paper Walkthrough

Comprehensive walkthrough of the Variational AutoEncoder research paper, explaining key concepts, mathematical foundations, and practical applications in deep learning and generative modeling.

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

Building a Dog Breed Identifier App From Scratch - DogNet

Learn to build a dog breed identifier app from scratch, covering data collection, model training, and deployment to the Google Play Store.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

Building Our First Deep Learning App From Scratch - Hello MNIST

Develop a deep learning app for digit recognition using MNIST dataset, covering model creation, app development, and publishing on the Google Play Store.

• YouTube
• 2 hours 27 minutes
• On-Demand
• Free Video

Mean Average Precision Explained and PyTorch Implementation

Learn to calculate and implement Mean Average Precision (mAP) for evaluating object detection models, with a detailed explanation and hands-on PyTorch implementation from scratch.

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

Intersection Over Union Explained and PyTorch Implementation

Comprehensive guide to Intersection over Union (IoU) in object detection, covering theory and practical implementation in PyTorch. Ideal for understanding this crucial metric.

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

TensorFlow Tutorial - Model Subclassing with Keras - Part 8

Learn to build flexible TensorFlow models using Keras subclassing, including a ResNet-like model with skip connections. Gain advanced model creation skills beyond Sequential and Functional APIs.

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

Pytorch Seq2Seq with Attention for Machine Translation

Build a Seq2Seq model with Attention in PyTorch for German-to-English machine translation, applying it to the Multi30k dataset and learning from scratch.

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

Pytorch Text Generator With Character Level LSTM

Learn to build a character-level LSTM text generator in PyTorch, focusing on generating new baby names. Explore practical implementation of RNNs for creative text generation tasks.

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

Neural Network from Scratch - Machine Learning Python

Implement a neural network using Python and numpy, focusing on the coding aspects while building upon previously explained mathematical concepts.

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

K-Nearest Neighbor From Scratch - Machine Learning Python

Implementación desde cero del clasificador K-Nearest Neighbor en Python, incluyendo una versión intuitiva y otra eficiente sin bucles para el aprendizaje automático.

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

Pytorch ResNet Implementation from Scratch

Learn to implement ResNet models (ResNet50, ResNet101, ResNet152) from scratch using PyTorch. Gain insights into the architecture and practical coding techniques for deep learning.

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

PyTorch GoogLeNet - InceptionNet Implementation from Scratch

Learn to implement GoogLeNet/InceptionNet from scratch in PyTorch, with explanations of network architecture and step-by-step coding guidance.

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

Cryptography - Hill Cipher Python

Learn to implement the Hill cipher encryption algorithm in Python, with step-by-step explanations and code examples for this challenging cryptographic technique.

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

Neural Network from Scratch with Python - Part 4

Implement a neural network using Numpy, learning to build deep learning models from the ground up without relying on high-level frameworks.

• YouTube
• 21 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