README.md

metadata

title: AI Learning
emoji: 🐝
colorFrom: yellow
colorTo: gray
sdk: docker
app_port: 7860
pinned: false
short_description: From perceptrons to the Nectar SDK detection workflow.

AI Learning — Black Bee Drones

A Next.js + TypeScript presentation that walks from "what is AI" to a deep tour of the Nectar SDK detection workflow. Designed as a live, in-room talk to a teammate joining from the hardware side.

Hosted at https://huggingface.co/spaces/blackbeedrones/ai-learning.

Run locally

npm install
npm run dev          # http://localhost:3000

Production build identical to what the Space runs:

docker build -t ai-learning .
docker run --rm -p 7860:7860 ai-learning
# open http://localhost:7860

Navigation

• Cover (/) lists every chapter.
• Inside a chapter:
  • → / Space — next slide (rolls into next chapter at the end)
  • ← — previous slide
  • ↑ / ↓ — previous / next chapter
  • Dots in the footer — jump to a specific slide

Layout

ai-learning/
├─ app/                          # Next.js App Router
│  ├─ page.tsx                   # Cover
│  └─ chapter/[slug]/page.tsx    # SlideRunner over a chapter manifest
├─ content/
│  ├─ chapters.ts                # Ordered chapter list
│  └─ slides/                    # One .tsx per chapter, slide objects
├─ components/
│  ├─ chrome/                    # SlideChrome · ProgressDots · CoverKeys
│  ├─ slide/                     # Slide · SlideRunner
│  ├─ math/                      # KaTeX wrappers
│  ├─ ui/                        # Kbd · Callout · CodeBlock
│  └─ viz/                       # ≈ 30 visualisation primitives
├─ lib/
│  ├─ hooks/                     # useKey · useReducedMotion · useInView
│  └─ utils.ts
├─ Dockerfile                    # HF Space build (Node 20-slim)
├─ next.config.mjs               # output: "standalone"
└─ tailwind.config.ts

Chapters (15, five parts)

Part	#	Slug	Title
I	1	what-is-ai	What is AI
I	2	data	Data
I	3	paradigms	Learning paradigms
II	4	classical-ml	Classical machine learning
II	5	deep-learning	Deep learning foundations
II	6	frameworks	Frameworks and ecosystem
II	7	convolutional-networks	Convolutional networks
III	8	cv-tasks	Computer vision tasks
III	9	classification	Image classification
IV	10	detection	Object detection
IV	11	segmentation	Segmentation
V	12	lifecycle	Training and evaluation
V	13	deployment	Deployment to the edge
V	14	nectar	The Nectar AI module
V	15	references	References

Lesson path

• Cover offers Lesson path (?path=lesson) for core slides only.
• Full deck includes reference and deep-dive slides for self-study.
• See content/STYLE.md for copy conventions.

Stack

• Next.js 14 (App Router) + TypeScript, strict mode
• Tailwind CSS with custom design tokens
• Framer Motion for transitions and primitive animations
• KaTeX for inline / block math
• HTML Canvas for the convolution, augmentation gallery, loss surface, decision boundary
• D3 reserved for future curves (light dependency)

Editing content

Each chapter lives in content/slides/chXX-*.tsx as an array of Slide objects. To add or reorder slides, edit the array — no router changes needed. The slide manifest contract is in components/slide/types.ts.

Reduced motion

Auto-running animations (loss surface, convolution, augmentations, agent loop, gradient descent) honour prefers-reduced-motion: reduce and either freeze on a representative frame or stop iterating.

License

For internal Black Bee Drones use.