#jupyter_notebook #control #course #course_materials #jupyter #jupyter_notebooks #latex #lecture #lecture_notes #machine_learning #online_learning #online_videos #open_education #open_education_resources #open_educational_resources #prediction #python #reinforcement_learning #teaching #teaching_materials #tutorial
https://github.com/upb-lea/reinforcement_learning_course_materials
https://github.com/upb-lea/reinforcement_learning_course_materials
GitHub
GitHub - upb-lea/reinforcement_learning_course_materials: Lecture notes, tutorial tasks including solutions as well as online videos…
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University - upb-lea/reinforcement_learning_course_materials
#other #blog_article #book #hacktoberfest #learn #rust #teaching #tutorial #video
https://github.com/ctjhoa/rust-learning
https://github.com/ctjhoa/rust-learning
GitHub
GitHub - ctjhoa/rust-learning: A bunch of links to blog posts, articles, videos, etc for learning Rust
A bunch of links to blog posts, articles, videos, etc for learning Rust - ctjhoa/rust-learning
#typescript #agent #agent_development #ai_agent #claude #claude_code #educational #llm #python #teaching #tutorial
Claude Code is an AI agent framework that uses a simple loop: send messages to Claude, check if it needs tools, execute those tools, and repeat. The benefit is that you can build powerful autonomous agents by layering one feature at a time—from basic tool use to multi-agent teams—without rewriting the core loop. This modular approach lets you start simple with bash commands and scale to complex workflows with planning, skill loading, background tasks, and team coordination, making it easier to automate development work and delegate entire projects to AI agents.
https://github.com/shareAI-lab/learn-claude-code
Claude Code is an AI agent framework that uses a simple loop: send messages to Claude, check if it needs tools, execute those tools, and repeat. The benefit is that you can build powerful autonomous agents by layering one feature at a time—from basic tool use to multi-agent teams—without rewriting the core loop. This modular approach lets you start simple with bash commands and scale to complex workflows with planning, skill loading, background tasks, and team coordination, making it easier to automate development work and delegate entire projects to AI agents.
https://github.com/shareAI-lab/learn-claude-code
GitHub
GitHub - shareAI-lab/learn-claude-code: Bash is all you need - A nano Claude Code–like agent, built from 0 to 1
Bash is all you need - A nano Claude Code–like agent, built from 0 to 1 - shareAI-lab/learn-claude-code