This comprehensive guide explains how to set up Visual Studio Code (VS Code) for remote development on an Ubuntu machine using SSH. This setup enables you to develop directly on remote servers while maintaining the comfort of your local VS Code environment.

Overview​

Remote development with VS Code over SSH provides several benefits:

• Direct server development: Edit files directly on the remote machine
• Consistent environment: Use your local VS Code setup with remote resources
• Security: Encrypted SSH connection protects your work
• Flexibility: Access powerful remote machines from any local device

Prerequisites​

• VS Code installed on your local machine
• Ubuntu machine with network access
• Administrator privileges on both machines

This comprehensive guide covers setting up a complete Ubuntu development environment, including package managers, development tools, GPU support, and machine learning frameworks.

This comprehensive guide explains how to install Ubuntu on a USB drive with a portable GRUB bootloader configuration. This setup allows you to run Ubuntu from any computer while keeping the host system's bootloader intact.

Overview​

Installing Ubuntu on a USB drive provides several advantages:

• Portability: Run your Ubuntu environment on any compatible computer
• Non-invasive: No changes to the host computer's internal storage
• Isolation: Complete separation from host operating system
• Development Environment: Portable development setup for embedded systems
• Recovery Tool: Bootable Ubuntu system for system recovery tasks

Understanding the Boot Process​

Traditional Installation vs USB Installation​

Traditional Installation:

• GRUB installed on internal disk
• EFI files stored in host system's ESP (EFI System Partition)
• GRUB menu appears even without USB drive

USB Installation (This Guide):

• GRUB installed entirely on USB drive
• EFI files contained within USB drive
• Host system remains unchanged
• GRUB only appears when USB is connected

Boot Flow Diagram​

Problem and Background​

Titanic - Machine Learning from Disaster

Problem: Create a machine learning model to predict which passengers survived the Titanic disaster.

Background: According to the Kaggle competition "Titanic - Machine Learning from Disaster" description: "On April 15, 1912, during her maiden voyage, the widely considered 'unsinkable' RMS Titanic sank after colliding with an iceberg. Unfortunately, there weren't enough lifeboats for everyone onboard, resulting in the death of 1502 out of 2224 passengers and crew."

While there was an element of luck involved, certain groups of people were more likely to survive than others, such as women, children, and the upper-class.

Machine Learning Final Report Name: YANG GUANGZE Student ID: 20T1126N

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