Tags

Every article is tagged from a controlled vocabulary of three tiers: domain (which part of the work it belongs to), technique (what method it covers), and tool (what it is built with). Domain tags cross-link material that the navigation separates, so an article applying machine learning to satellite imagery appears under both.

AI & Machine Learning

• Bias-Variance
• Embeddings Across Domains
• Fine-Tuning
• From Computer Vision to Remote Sensing: A 2026 Model Landscape
• GPU & Distributed Training
• Geospatial PEFT
• LLM Inference & KV-Cache
• Precision-Recall
• PyTorch Fundamentals
• Statistics to Deep Learning
• Temperature & Sampling
• Tokenization & Embeddings
• Transformers & Attention
• ViT Data Requirements
• Vision Transformers

CUDA

• GPU & Distributed Training
• vLLM on HPC

Claude Code

• Claude Code Across a Laptop and an HPC Cluster

Computer Vision

• From Computer Vision to Remote Sensing: A 2026 Model Landscape
• ViT Data Requirements
• Vision Transformers

Coordinate Systems

• Coordinate Reference Systems

Dask

• Multi-Node Parallelization

Data Engineering

• Coordinate Reference Systems
• Geospatial Python Stack
• Production Geospatial Patterns

Deep Learning

• Bias-Variance
• Fine-Tuning
• GPU & Distributed Training
• PyTorch Fundamentals
• Statistics to Deep Learning
• Transformers & Attention
• ViT Data Requirements
• Vision Transformers

Distributed Computing

• GPU & Distributed Training
• Multi-Node Parallelization

Embeddings

• Embeddings Across Domains
• Tokenization & Embeddings

Fine-Tuning

• Fine-Tuning
• Geospatial PEFT

Foundation Models

• Embeddings Across Domains
• From Computer Vision to Remote Sensing: A 2026 Model Landscape
• Geospatial PEFT

GeoPandas

• Geospatial Python Stack
• Interactive Visualization with hvPlot

Geospatial & Remote Sensing

• Coordinate Reference Systems
• Embeddings Across Domains
• From Computer Vision to Remote Sensing: A 2026 Model Landscape
• Geospatial PEFT
• Geospatial Python Stack
• Hyperspectral Sensor Physics
• Interactive Visualization with hvPlot
• Production Geospatial Patterns
• State Estimation & Kalman Filtering

HPC & Infrastructure

• Claude Code Across a Laptop and an HPC Cluster
• GPU & Distributed Training
• Linux Shell Setup
• Multi-Node Parallelization
• Ollama on HPC
• vLLM on HPC

Inference

• LLM Inference & KV-Cache
• Ollama on HPC
• Temperature & Sampling
• vLLM on HPC

LLM

• LLM Inference & KV-Cache
• Ollama on HPC
• Temperature & Sampling
• Tokenization & Embeddings
• Transformers & Attention
• vLLM on HPC

Model Evaluation

• Bias-Variance
• Precision-Recall

NLP

• Tokenization & Embeddings

Practice & Tooling

• Claude Code Across a Laptop and an HPC Cluster
• Linux Shell Setup
• Ollama on HPC

PyTorch

• Fine-Tuning
• GPU & Distributed Training
• PyTorch Fundamentals

Rasterio

• Geospatial Python Stack
• Production Geospatial Patterns

Remote Sensing

• From Computer Vision to Remote Sensing: A 2026 Model Landscape
• Hyperspectral Sensor Physics
• Precision-Recall

SLURM

• Multi-Node Parallelization

State Estimation

• State Estimation & Kalman Filtering

Transformers

• From Computer Vision to Remote Sensing: A 2026 Model Landscape
• LLM Inference & KV-Cache
• Tokenization & Embeddings
• Transformers & Attention
• ViT Data Requirements
• Vision Transformers

Visualization

• Interactive Visualization with hvPlot

Xarray

• Geospatial Python Stack
• Interactive Visualization with hvPlot
• Production Geospatial Patterns