Multi-Head Attention
How multi-head attention runs scaled dot-product attention in parallel across several representation subspaces to build context-aware token embeddings.
7 min readConcept
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Neural Nets
Explore machine learning concepts related to Neural Nets. Clear explanations and practical insights.
6
Concepts Found
Concepts Related to Neural Nets
Positional Embeddings in Vision Transformers
Explore how positional embeddings enable Vision Transformers (ViT) to process sequential data by encoding relative positions.
6 min readConcept
Self-Attention in Vision Transformers
Follow one image patch through Q/K/V projection, scaled scores, row-wise softmax, value mixing, and the residual update inside a Vision Transformer.
10 min readConcept
Convolution Operation: The Foundation of CNNs
Interactive guide to convolution in CNNs: visualize sliding windows, kernels, stride, padding, and feature detection with step-by-step demos.
10 min readConcept
Dilated Convolutions: Expanding Receptive Fields Efficiently
Understand dilated (atrous) convolutions: how dilation rates expand receptive fields exponentially without extra parameters and how to avoid gridding artifacts.
10 min readConcept
VAE Latent Space: Understanding Variational Autoencoders
Explore VAE latent space in deep learning. Learn variational autoencoder encoding, decoding, interpolation, and the reparameterization trick.
4 min readConcept