陆昱宽

Sources:

1. --> How To Install Rust on Ubuntu 20.04

Sources:

1. How To Install Node.js on Ubuntu 20.04

Sources:

1. NvChad
2. NvChad --- Rocky Linux
3. Dreams of Code's NvChad playlist
4. BrunoKrugel's Github repo

Note: This article will only focus on NvChad itself. If you want to simply copy my computer configs (ALL OF THEM), you can refer to How to Set Up on A New Machine.

Note: It's highly recommended to install an AI agent on your server first and let it to condifure everhthing for you. This docuement should serve as a good referrence for both human and agents.

How to set up configs on a new machine (typically a ubuntu server).

My dotfiles are save in:

https://github.com/LYK-love/dotfiles-for-servers

For the usage of most of the rust tools, see my Unix CLI Tools.

1. Shiyu Zhao. Chapter 4: Value Iteration and Policy Iteration. Mathematical Foundations of Reinforcement Learning.
2. --> Youtube: Value Iteration and Policy Iteration

This chapter introduces three algorithms that are closely related to each other. Briefly speaking, they are all solutions of Bellman optimality equations (BOEs) to get optimal policies.

1. Shiyu Zhao. Chapter 3: Bellman Optimality Equation. Mathematical Foundations of Reinforcement Learning.
2. --> Youtube: Bellman Optimality Equation
3. --> Youtube: How to Solve Bellman Optimality Equation

The previous chapter introduced the Bellman equation of any given policy. The present post introduces the Bellman optimality equation, which is a special Bellman equation whose corresponding policy is optimal. By solving

Sources:

1. Shiyu Zhao. Chapter 2: State Values and Bellman Equation. Mathematical Foundations of Reinforcement Learning.
2. --> Youtube: Bellman Equation: Action Value

Sources:

• Masked Autoencoders (MAE)
• Vision Transformer (ViT)
• Segment Anything blog
• Github: SAM
• Youtube video: Segment Anything - Model explanation with code
  • -->Slides

• Cross entropy
• Focal loss
• Hinge loss
• ...

Sources:

1. Shiyu Zhao. Chapter 1: Basic Concepts. Mathematical Foundations of Reinforcement Learning.
2. OpenAI Spinning Up