Computer Vision: Why It Matters and Which Libraries to Learn
A practical introduction to computer vision, its main tasks, and the Python libraries worth learning for real projects.
Blog · Anupam Shakya
RSS feedIdeas under
observation.
Essays, experiments, and learning notes about artificial intelligence, computer vision, medical imaging, software, research, space, and the questions that connect them.
What I write about
Six connected areas, from systems we build to the universe we inhabit.
01AI
Intelligent systems, models, evaluation, and the questions behind them.
1 post 02Computer VisionImages, perception, medical imaging, segmentation, and visual learning.
1 post 03EngineeringFull-stack systems, architecture, implementation, and lessons from building.
0 posts 04ML / DLMachine learning, deep learning, experiments, papers, and practical intuition.
2 posts 05SpaceAstronomy, cosmology, scale, time, and our place in the universe.
1 post 06ThoughtsCuriosity, learning, research life, uncertainty, and ideas still taking shape.
2 postsComputer Vision7 min read
Computer Vision: Why It Matters and Which Libraries to Learn
A practical introduction to computer vision, its main tasks, and the Python libraries worth learning for real projects.
OpenCVPyTorch
Thoughts3 min read
Everyone Seems Ahead From Far Away
A simple thought about comparison, quiet progress, and the feeling that everyone else has already figured life out.
LifeComparison
ML / DL9 min read
Machine Learning and Deep Learning: The Complete Concept Map
A structured guide to the main ML and DL concepts, from data and evaluation to neural networks, transformers, and deployment.
Machine LearningDeep Learning
ML / DL8 min read
Machine Learning for Satellite Imaging: Teaching Models to Read Earth
How ML and deep learning turn multispectral satellite data into maps of land, water, crops, cities, disasters, and change.
SpaceSatellite Imaging
Space5 min read
The Light Before Everything Went Dark
We can look billions of years into the past, but the universe has hidden its first moments behind a wall no telescope can see through.
CosmologyCosmic Microwave Background
AI10 min read
Kimi K3 Open Weights Are Live: 2.8T Parameters, 1M Context, Hardware Requirements
Moonshot AI's 2.8-trillion-parameter Kimi K3 is open-weight and multimodal. Here is what it offers—and the hardware needed to run it.
Kimi K3Open Weights
Thoughts2 min read
Why I Built This Blog
A place to think in public about intelligent systems, visual understanding, software, research, and the universe beyond all of them.
LearningResearch