Projects

 · 335 words · 2 min · Pbulished On: October 4, 2022 (Last updated on: October 17, 2022)

Personal Project: My HomeLab and My Cluster

These articles are inside my projects: My Disbributed HomeLab and My HA K3s cluster

  1. Homelab: My Devices
  2. Homelab: My Distributed Homelab
  3. Homelab: My Network setup
  4. Homelab: Don’t Let the Docker escape from the ufw’s control
  5. Homelab: How to build a AIO home-server
  6. Homelab: My Distributed Homelab (2)
  7. Homelab: A self-hosted GitHub Accelerator
  8. K3s/Kubernetes: A quick setup for single machine
  9. K3s/Kubernetes: A quick setup for HA
  10. K3s/Kubernetes: A self-hosted registry
  11. K3s/Kubernetes: How GitOps works - Coming soon
  12. K3s/Kubernetes: From K3s to Kubernetes: Set up a Kubernetes in a nutshell
  13. K3s/Kubernetes: Build a High availability Kubernetes Cluster with Kubeadm

Personal Project: Personal Experimental Network: L-Net

These articles are inside my projects: Build a Experimental Network with your VPS

  1. L-Net: My Experimental Network V1.0 - BGP and OSPF
  2. L-Net: My Experimental Network v1.1 - eBGP and iBGP
  3. L-Net: My Experimental Netwrok v1.2 - VXLAN over Wireguard

Machine Learning with Us

Previously, this project is called: Medical Image arounds Us: Deep Learning with Medical Image Processing(MIP)

These articles are introducing the paper I read and the code I reproduce in Medical Image Analysis/Processing. More generally, medical image processing is a subset of image processing or computer vision, or a subset in machine learning and deep learning. Therefore, I would also post some of the paper ouside the MIP but inside the ML/DL. All the reference literatures and notes can be found in Academic Literature

  1. RetiGAN: A GAN-based model on retinal Image synthesis
  2. Style Transfer and Synthesis (1/3): Style Transfer in Image Synthesis
  3. Style Transfer and Synthesis (2/3): From Decomposition to Generative Model (coming soon)

Foundation of Mathematics, Statistics and Computer Science

Mathematics and CS-related knowledge and technique are vitually important for someone who want to dive deeper in Machine Learning and other related Subjects, thus, I would like to build up a knowledge base in both math and cs and programing implementation with mainly R and Python. The reason we choose

  1. Knowledge base
    1. Mathematics
    2. Statistics
    3. Computer Science
  2. Correlated code: Course We Need