Feature Pyramid Networks (FPN) Explained
Learn how Feature Pyramid Networks build multi-scale feature representations through top-down pathways and lateral connections for robust object detection.
10 min readConcept
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Architectures
Explore machine learning concepts related to Architectures. Clear explanations and practical insights.
22
Concepts Found
Concepts Related to Architectures
CLS Token in Vision Transformers
Trace how a learned CLS row joins image patches, gathers evidence through self-attention, and becomes the image-level classification readout.
7 min readConcept
How RAM Works: Interactive Deep Dive into Computer Memory
Explore the inner workings of RAM through beautiful animations and interactive visualizations. Understand memory cells, addressing, and the memory hierarchy.
12 min readConcept
Hierarchical Attention in Vision Transformers
Trace how local windows, shifted cross-window exchange, and patch merging turn one high-resolution token grid into a multi-scale vision hierarchy.
10 min readConcept
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
Linux Kernel Architecture: How Your OS Actually Works
Linux kernel architecture explained. Learn syscalls, protection rings, user vs kernel space, and what happens when you run a command.
12 min readConcept
Positional Embeddings in Vision Transformers
Explore how positional embeddings enable Vision Transformers (ViT) to process sequential data by encoding relative positions.
6 min readConcept
Batch Norm vs Layer Norm: When to Use Which
BatchNorm normalizes over the batch and spatial axes; LayerNorm normalizes over the channel and spatial axes for each sample. The choice changes whether your model trains stably with batch=1, depends on batch composition at inference, and behaves consistently across train and eval.
8 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
Virtual Memory & TLB: Complete Guide to Address Translation
Master virtual memory and TLB address translation with interactive demos. Learn page tables, page faults, and memory management optimization.
16 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
Receptive Field in CNNs
Understand receptive fields in CNNs: how convolutional layers expand their field of view and the gap between theoretical and effective receptive fields.
7 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
Flynn's Classification: Taxonomy of Computer Architectures
Flynn's Classification explained — SISD, SIMD, MISD, MIMD with interactive architecture explorer, SIMD evolution from MMX to AMX, branch divergence visualization, and workload-architecture throughput comparison.
15 min readConcept
CPU Pipelines & Branch Prediction in Processors
Explore CPU pipeline stages, instruction-level parallelism, pipeline hazards, and branch prediction through interactive visualizations.
8 min readConcept
Hazard Detection: Pipeline Dependencies and Solutions
Master pipeline hazards through interactive visualizations of data dependencies, control hazards, structural conflicts, and advanced detection mechanisms.
14 min readConcept
Adaptive Tiling: Efficient Visual Token Generation
Learn adaptive tiling in vision transformers: dynamically partition images based on visual complexity to reduce token counts while preserving detail.
7 min readConcept
Memory Controllers: The Brain Behind RAM Management
Learn how memory controllers manage CPU-RAM data flow. Interactive demos of channels, ranks, banks, and command scheduling for optimal bandwidth.
18 min readConcept
Memory Interleaving: Parallel Memory Access
Discover how memory interleaving distributes addresses across banks for parallel access. Boost memory bandwidth in DDR5 and GPU systems.
6 min readConcept
NUMA Architecture: Non-Uniform Memory Access
Explore NUMA architecture and memory locality in multi-socket systems. Understand local vs remote memory access latency and optimization strategies.
8 min readConcept
Skip Connections in Neural Networks
Learn how skip connections and residual learning enable training of very deep neural networks. Understand the ResNet revolution with interactive visualizations.
9 min readConcept