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Computing Platforms: Set up the Workspace for Machine Learning Projects

Google Colab, Kaggle Kernel, Visual Machine, and others (docker, local, etc.)

Published onNov 06, 2022
Computing Platforms: Set up the Workspace for Machine Learning Projects

Part I: Tech Editors

Read more about a comprehensive resource list of tech editors here:

1. GitHub Readme

  • [GitHub Readme] A README file is an introductory file to your project, often displayed on the main page of your GitHub repository. Check [This Website] for guidelines to write a good README file. The GitHub README file supports most Markdown language features. However, some functions like a table of contents are not supported. Check [This Website] for instructions.

2. Markdown

Markdown is an easy-to-use language standard that allows you to create structured documents. Check [Markdown Tutorial] to get started with Markdown.

  • Language Basic

    • [Markdown Guideline] The syntax for Markdown language is very simple. Check the link for a quick syntax reference.

      Markdown Crash Course

3. Whimsical

  • [Whimsical] Whimsical is a handy, easy-to-use web application for creating beautiful and neat graphical content such as a flowchart. Check out their [official YouTube channel] for more details.

working folder for Stats201, Autumn 2022:

Getting to know Whimsical

4. Canva

  • [Canva] Canva is a graphic design platform that can be used for various types of visual content. Check this [YouTube video] to get started.

8. Designing your Poster in Canva | Skills

5. GitHub Page

  • [GitHub Page] is the webpage hosted directly from your GitHub repositories. Check this [YouTube video] to create and publish your own sites.

What is GitHub Pages?

Part II: Computing Platforms

Read more about software and packages for empirical studies here:

1. Google Colab (Code)

Google Colab Tutorial for Beginners | Get Started with Google Colab
How to Query the Ethereum Blockchain (like Etherscan) using Web3
Web3py Full Tutorial
How to query the ethereum mempool with

2. Kaggle Kernel (Data)

3. Visual Machine (Environment)

3.1. What is a VM and how is it useful in collaborative learning/research/innovation?

3.2. What is an IDE and how is it useful in collaborative learning/research/innovation?

3.3. How to set up the workplace of VM and IDE

1. Set up VS code

  • VS code [Short-Cut]

  • Download and install VS code on your local computer: [Doc][Video: Mac and Windows]

    • Python and Anaconda: [Anaconda Doc][Video]

    • Python related Extensions:Python, Pylance, Jupyter, Jupyter Keymap, Python Indent, Indent-rainbow, Bracket Pair Colorizer 2, Code Spell Checker, Markdown all in one, Excel viewer, Rainbow csv

    • Code sharing Extensions: Live Share Extension Pack

    • VM remote Control Extensions: Remote -SSH

  • Check milestones [Video]

    • Install the correct version of Python [Video] and PiP[]

    • Show Command Palette [Ctrl+Shift+P] and Choose the Python environment from the drop-down menu to work with

    • Show Command Palette [Ctrl+Shift+P] and Choose to create new python notebook from the drop-down menu

2. Connect VS code to a VM

  • Credentials:

    • IP address: What is the IP? An Internet Protocol address (IP address) is a numerical label such as that is connected to a computer network that uses the Internet Protocol for communication. An IP address serves two main functions: network interface identification and location addressing.

    • username and password.

  •  VM on VS code via SSH: SSH, also known as Secure Shell or Secure Socket Shell, is a network protocol that gives users, particularly system administrators, a secure way to access a computer over an unsecured network. [Video]

  •  Install Python and Extensions on VM [Linux Cheat Sheet][Video]: Python and Anaconda: Basically you need to go through “1. Set up VS code” again.

  1. Sync Project with GitHub [Video]:

    • Create a Blank GitHub Repository: [Doc][Our Course Repo]

    • Set up SSH connection between GitHub repository and the VS code: [Video][Docs]

    • Clone to the VM in VS code command window

    In Command Window Type: git clone [address]

    • Commit and Push to GitHub for updates [Video]

1. Stanford Encyclopedia of Philosophy (Principle)

Does More Core Means Better Performance? | CPU Cores & Threads Explained
6. Multicore Programming
  • Storage

Memory & Storage: Crash Course Computer Science #19
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