CodeEmporium Courses

Informer: Complete Code from Scratch - Time Series Transformer Analysis

Line-by-line exploration of the time series transformer, focusing on implementation details and code structure for deep learning enthusiasts and practitioners.

• YouTube
• 1 hour 27 minutes
• On-Demand
• Free Video

Informer Architecture Explained - Complete Guide

Comprehensive exploration of Informer encoder architecture, detailing its components and implementation for advanced time series forecasting and sequence modeling tasks.

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

Informer Encoder Architecture Explained

Explore the Informer Encoder architecture, its key components, and implementation details for advanced time series forecasting and sequence modeling tasks.

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

Generative AI - Explained

Explore generative AI's unique features and how it differs from other AI buzzwords in this concise, informative video.

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

Generative AI, ChatGPT, and LLMs - Buzzwords Explained

Clarifies key AI terms: genAI, ChatGPT, and LLMs. Demystifies buzzwords, explaining differences and relationships between these concepts in artificial intelligence.

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

Primary Visual Cortex: How Brain Processes What We See

Discover how the primary visual cortex processes visual information, from retina to brain, exploring Hubel and Wiesel's experiments on simple and complex cells that detect features in what we see.

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

Where Did Convolution Networks Come From? - Evolution from Neo-Cognitron to Modern CNNs

Discover the biological origins of convolutional neural networks through Hubel & Wiesel's experiments and the Neo-cognitron, understanding why CNNs use convolution, activation, and pooling.

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

Pointwise Convolutions - Explained with Code

Discover 1x1 convolutions in neural networks through architecture diagrams and PyTorch implementation, exploring their benefits for dimensionality reduction and computational efficiency.

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

VGGNet - Deep Convolutional Neural Network Architecture Explained

Explore VGGNet architecture fundamentals: understand its depth, 3x3 convolution advantages, coding implementation, and performance comparison with AlexNet in this comprehensive tutorial.

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

Inception Network - Explained with Code

Explore the Inception network architecture, understand its unique design principles, and implement it with hands-on coding to see how this funky-looking neural network achieves superior performance.

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

ADALINE - Understanding Adaptive Linear Neurons and Their Role in Deep Learning

Explore the historical foundations of deep learning through ADALINE (Adaptive Linear Neurons), understanding its key concepts, implementation, and comparison with perceptrons from a 1960s electrical engineering perspective.

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

Understanding Hopfield Networks - Architecture and Memory Systems

Delve into the foundational concepts of Hopfield Networks, exploring their architecture, memory storage mechanisms, and practical applications in neural network design and associative memory systems.

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

Back Propagation by Hand - The Math You Should Know

Master the mathematical foundations of back propagation through detailed hand calculations, covering forward/backward passes, gradient computation, and weight updates with verification.

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

Fast R-CNN - Explained

Explore Fast R-CNN architecture, training methods, and inference techniques for improved object detection performance compared to original R-CNN networks.

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

ResNet - Explained

Discover ResNet architecture and skip connections to solve vanishing gradients and performance degradation in deep neural networks with practical code examples.

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